# select, filter, %>%
library(dplyr)

## `parse_quosure`
library(rlang)

data <- read.csv('data/payments_ppdb_app_category_code_aggregated_LT01.csv')

## Only first cluster
x <- data %>% filter(age >= 50 & 0 < approval_real_price_sum_by_by_approval_type_LT01)
target <- x %>% select(approval_real_price_sum_by_by_approval_type_LT01)

category_code <- x %>% select(matches("^category_code_LT01_\\d{1,2}_count$")) %>% cbind(target)

for(i in seq(2, 6)) {
  cat("i: ", i, '\n')
  combinations <- combn(16, i)
  for(j in seq(ncol(combinations))) {
    # cat("j: ", j, '\n')
    comb.vector <- combinations[,j]
    comb.representation <- paste(paste0('category_code_LT01_', comb.vector, '_count'), collapse = '+')
    tmp <- category_code %>% mutate(new_category_count_col = UQ(parse_quosure(comb.representation)))

    single.formula_str <- paste('approval_real_price_sum_by_by_approval_type_LT01 ~ new_category_count_col')
    single.summary.object <- ((tmp + 1) %>% log %>% lm(single.formula_str %>% as.formula, .) %>% summary)
    if(single.summary.object$adj.r.squared > 0.7) {
      cat('########################################\n')
      cat(comb.representation, '\n')
      cat(paste(single.formula_str, single.summary.object$adj.r.squared, '\n'))
      print(single.summary.object)
      cat('########################################\n')
    }

    multiple.formula_str <- paste('approval_real_price_sum_by_by_approval_type_LT01 ~ ', comb.representation)
    multiple.summary.object <- ((tmp + 1) %>% log %>% lm(multiple.formula_str %>% as.formula, .) %>% summary)
    if(multiple.summary.object$adj.r.squared > 0.6) {
      cat('########################################\n')
      cat(comb.representation, '\n')
      cat(paste(multiple.formula_str, multiple.summary.object$adj.r.squared, '\n'))
      print(multiple.summary.object)
      cat('########################################\n')
    }
  }
}
## i:  2 
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count 0.609930794153804 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0518 -0.7622 -0.0038  0.9382  4.0296 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                10.01233    0.08835  113.33   <2e-16 ***
## category_code_LT01_4_count  1.10057    0.06484   16.97   <2e-16 ***
## category_code_LT01_5_count  0.94441    0.06261   15.09   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 495 degrees of freedom
## Multiple R-squared:  0.6115, Adjusted R-squared:  0.6099 
## F-statistic: 389.6 on 2 and 495 DF,  p-value: < 2.2e-16
## 
## ########################################
## i:  3 
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count 0.618577686520257 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0258 -0.7994  0.0041  0.8836  3.4490 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94420    0.08822 112.719  < 2e-16 ***
## category_code_LT01_1_count  0.44824    0.08263   5.425 9.11e-08 ***
## category_code_LT01_2_count  0.84631    0.07027  12.044  < 2e-16 ***
## category_code_LT01_5_count  1.00516    0.06091  16.504  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 494 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.6186 
## F-statistic: 269.7 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count 0.618512370116477 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0272 -0.7681 -0.0092  0.9314  3.8490 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97858    0.08791 113.514  < 2e-16 ***
## category_code_LT01_1_count  0.30914    0.08874   3.484 0.000539 ***
## category_code_LT01_4_count  0.94359    0.07837  12.039  < 2e-16 ***
## category_code_LT01_5_count  0.95758    0.06203  15.437  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 494 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6185 
## F-statistic: 269.6 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count 0.611841986963208 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0309 -0.7641  0.0094  0.8695  3.8264 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97454    0.08857  112.61  < 2e-16 ***
## category_code_LT01_2_count  0.83284    0.07588   10.98  < 2e-16 ***
## category_code_LT01_3_count  0.49328    0.10937    4.51 8.09e-06 ***
## category_code_LT01_5_count  0.96875    0.06205   15.61  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 494 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6118 
## F-statistic: 262.1 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count 0.638158949842913 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9820 -0.7482  0.0436  0.8466  3.4639 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95865    0.08552 116.452  < 2e-16 ***
## category_code_LT01_2_count  0.54869    0.08718   6.294 6.83e-10 ***
## category_code_LT01_4_count  0.68801    0.09053   7.599 1.51e-13 ***
## category_code_LT01_5_count  0.92115    0.06041  15.248  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 494 degrees of freedom
## Multiple R-squared:  0.6403, Adjusted R-squared:  0.6382 
## F-statistic: 293.2 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count 0.605227057073404 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0422 -0.8156 -0.0034  0.9715  3.8209 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.98003    0.08933 111.719  < 2e-16 ***
## category_code_LT01_2_count  0.90695    0.07212  12.575  < 2e-16 ***
## category_code_LT01_5_count  0.97713    0.06262  15.605  < 2e-16 ***
## category_code_LT01_6_count  0.52736    0.15401   3.424 0.000668 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 494 degrees of freedom
## Multiple R-squared:  0.6076, Adjusted R-squared:  0.6052 
## F-statistic:   255 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count 0.610575099009888 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0617 -0.7836 -0.0125  0.9359  3.8042 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.99675    0.08854 112.903  < 2e-16 ***
## category_code_LT01_2_count  0.90205    0.06889  13.094  < 2e-16 ***
## category_code_LT01_5_count  0.98114    0.06185  15.862  < 2e-16 ***
## category_code_LT01_7_count  0.65740    0.15214   4.321 1.88e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 494 degrees of freedom
## Multiple R-squared:  0.6129, Adjusted R-squared:  0.6106 
## F-statistic: 260.7 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count 0.611645789740146 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0698 -0.7786 -0.0018  0.8929  4.2741 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00592    0.08843 113.152  < 2e-16 ***
## category_code_LT01_2_count   0.76145    0.08618   8.835  < 2e-16 ***
## category_code_LT01_5_count   0.97957    0.06178  15.855  < 2e-16 ***
## category_code_LT01_11_count  0.50568    0.11284   4.481 9.22e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 494 degrees of freedom
## Multiple R-squared:  0.614,  Adjusted R-squared:  0.6116 
## F-statistic: 261.9 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count 0.618313867410239 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0187 -0.7812  0.0320  0.8611  3.4256 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.99247    0.08758 114.091  < 2e-16 ***
## category_code_LT01_3_count  0.38829    0.11269   3.446 0.000618 ***
## category_code_LT01_4_count  0.92900    0.08120  11.441  < 2e-16 ***
## category_code_LT01_5_count  0.92523    0.06218  14.880  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 494 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.6183 
## F-statistic: 269.4 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 0.618001558003724 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0125 -0.7797 -0.0061  0.9293  4.0517 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.99015    0.08767 113.946  < 2e-16 ***
## category_code_LT01_4_count  0.98153    0.07317  13.414  < 2e-16 ***
## category_code_LT01_5_count  0.91967    0.06239  14.742  < 2e-16 ***
## category_code_LT01_6_count  0.50928    0.15045   3.385 0.000768 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 494 degrees of freedom
## Multiple R-squared:  0.6203, Adjusted R-squared:  0.618 
## F-statistic:   269 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 0.618158892682412 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0411 -0.7553  0.0053  0.8625  4.0313 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                10.01061    0.08741 114.521  < 2e-16 ***
## category_code_LT01_4_count  0.98522    0.07250  13.589  < 2e-16 ***
## category_code_LT01_5_count  0.93141    0.06206  15.008  < 2e-16 ***
## category_code_LT01_7_count  0.52660    0.15417   3.416 0.000689 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 494 degrees of freedom
## Multiple R-squared:  0.6205, Adjusted R-squared:  0.6182 
## F-statistic: 269.2 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 0.609308982558757 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0562 -0.7728 -0.0115  0.9483  4.0283 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                10.01362    0.08846 113.196   <2e-16 ***
## category_code_LT01_4_count  1.10149    0.06492  16.966   <2e-16 ***
## category_code_LT01_5_count  0.94883    0.06339  14.969   <2e-16 ***
## category_code_LT01_8_count -0.12833    0.27861  -0.461    0.645    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 494 degrees of freedom
## Multiple R-squared:  0.6117, Adjusted R-squared:  0.6093 
## F-statistic: 259.4 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 0.613667666108038 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0346 -0.7934  0.0204  0.9317  4.0380 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                10.00383    0.08799 113.687   <2e-16 ***
## category_code_LT01_4_count  1.05806    0.06691  15.814   <2e-16 ***
## category_code_LT01_5_count  0.93175    0.06253  14.901   <2e-16 ***
## category_code_LT01_9_count  0.54369    0.22599   2.406   0.0165 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 494 degrees of freedom
## Multiple R-squared:  0.616,  Adjusted R-squared:  0.6137 
## F-statistic: 264.2 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 0.611077212420303 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0110 -0.7808  0.0228  0.9257  3.8738 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97287    0.09174 108.712   <2e-16 ***
## category_code_LT01_4_count   1.07835    0.06628  16.270   <2e-16 ***
## category_code_LT01_5_count   0.94239    0.06253  15.071   <2e-16 ***
## category_code_LT01_10_count  0.17767    0.11330   1.568    0.117    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 494 degrees of freedom
## Multiple R-squared:  0.6134, Adjusted R-squared:  0.6111 
## F-statistic: 261.3 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 0.623135276287295 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0407 -0.7314  0.0308  0.9156  3.7053 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01171    0.08684 115.289  < 2e-16 ***
## category_code_LT01_4_count   0.84822    0.08680   9.773  < 2e-16 ***
## category_code_LT01_5_count   0.92925    0.06164  15.075  < 2e-16 ***
## category_code_LT01_11_count  0.46866    0.10942   4.283 2.22e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 494 degrees of freedom
## Multiple R-squared:  0.6254, Adjusted R-squared:  0.6231 
## F-statistic: 274.9 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 0.609920988143405 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0456 -0.8001  0.0020  0.9316  4.0314 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01052    0.08837 113.282   <2e-16 ***
## category_code_LT01_4_count   1.08226    0.06741  16.055   <2e-16 ***
## category_code_LT01_5_count   0.93811    0.06293  14.908   <2e-16 ***
## category_code_LT01_12_count  0.20620    0.20750   0.994    0.321    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 494 degrees of freedom
## Multiple R-squared:  0.6123, Adjusted R-squared:  0.6099 
## F-statistic:   260 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 0.609401773495551 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0508 -0.7625 -0.0053  0.9252  4.0299 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01201    0.08841 113.246   <2e-16 ***
## category_code_LT01_4_count   1.09324    0.06613  16.532   <2e-16 ***
## category_code_LT01_5_count   0.94343    0.06267  15.053   <2e-16 ***
## category_code_LT01_13_count  0.14189    0.24715   0.574    0.566    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 494 degrees of freedom
## Multiple R-squared:  0.6118, Adjusted R-squared:  0.6094 
## F-statistic: 259.5 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 0.609293242553254 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0515 -0.7870 -0.0033  0.9248  4.0279 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01394    0.08850 113.157   <2e-16 ***
## category_code_LT01_4_count   1.09317    0.06706  16.302   <2e-16 ***
## category_code_LT01_5_count   0.94155    0.06300  14.946   <2e-16 ***
## category_code_LT01_14_count  0.14590    0.33274   0.438    0.661    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 494 degrees of freedom
## Multiple R-squared:  0.6117, Adjusted R-squared:  0.6093 
## F-statistic: 259.4 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 0.609291533003517 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0520 -0.7689 -0.0043  0.9382  4.0296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01227    0.08842 113.235   <2e-16 ***
## category_code_LT01_4_count   1.09501    0.06614  16.557   <2e-16 ***
## category_code_LT01_5_count   0.94476    0.06266  15.077   <2e-16 ***
## category_code_LT01_15_count  0.33173    0.76083   0.436    0.663    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 494 degrees of freedom
## Multiple R-squared:  0.6116, Adjusted R-squared:  0.6093 
## F-statistic: 259.3 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 0.610052333152422 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0503 -0.7649 -0.0036  0.9386  4.0296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01226    0.08833 113.345   <2e-16 ***
## category_code_LT01_4_count   1.09532    0.06501  16.847   <2e-16 ***
## category_code_LT01_5_count   0.94235    0.06263  15.047   <2e-16 ***
## category_code_LT01_16_count  1.26824    1.18044   1.074    0.283    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 494 degrees of freedom
## Multiple R-squared:  0.6124, Adjusted R-squared:  0.6101 
## F-statistic: 260.2 on 3 and 494 DF,  p-value: < 2.2e-16
## 
## ########################################
## i:  4 
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count 0.62658896441048 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9945 -0.7743  0.0483  0.8309  3.4598 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93335    0.08735 113.721  < 2e-16 ***
## category_code_LT01_1_count  0.38093    0.08411   4.529 7.45e-06 ***
## category_code_LT01_2_count  0.72470    0.07816   9.272  < 2e-16 ***
## category_code_LT01_3_count  0.37584    0.11036   3.406 0.000714 ***
## category_code_LT01_5_count  0.97562    0.06088  16.024  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 493 degrees of freedom
## Multiple R-squared:  0.6296, Adjusted R-squared:  0.6266 
## F-statistic: 209.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count 0.643645047532432 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9654 -0.7660  0.0798  0.8576  3.4757 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93372    0.08529 116.469  < 2e-16 ***
## category_code_LT01_1_count  0.25310    0.08628   2.933  0.00351 ** 
## category_code_LT01_2_count  0.52100    0.08703   5.987 4.13e-09 ***
## category_code_LT01_4_count  0.58031    0.09706   5.979 4.31e-09 ***
## category_code_LT01_5_count  0.93311    0.06009  15.528  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.344 on 493 degrees of freedom
## Multiple R-squared:  0.6465, Adjusted R-squared:  0.6436 
## F-statistic: 225.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count 0.623677233945147 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9970 -0.8123  0.0407  0.9482  3.4607 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93243    0.08773 113.213  < 2e-16 ***
## category_code_LT01_1_count  0.41623    0.08288   5.022 7.16e-07 ***
## category_code_LT01_2_count  0.76236    0.07608  10.021  < 2e-16 ***
## category_code_LT01_5_count  0.98064    0.06114  16.039  < 2e-16 ***
## category_code_LT01_6_count  0.42120    0.15185   2.774  0.00575 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 493 degrees of freedom
## Multiple R-squared:  0.6267, Adjusted R-squared:  0.6237 
## F-statistic: 206.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count 0.627252540516555 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.7802  0.0411  0.9198  3.4452 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94795    0.08722 114.057  < 2e-16 ***
## category_code_LT01_1_count  0.39842    0.08289   4.807 2.04e-06 ***
## category_code_LT01_2_count  0.76397    0.07327  10.427  < 2e-16 ***
## category_code_LT01_5_count  0.98359    0.06052  16.253  < 2e-16 ***
## category_code_LT01_7_count  0.53397    0.15105   3.535 0.000446 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 493 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6273 
## F-statistic: 210.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count 0.617975830985733 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0302 -0.7930 -0.0003  0.9041  3.4478 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94539    0.08833 112.597  < 2e-16 ***
## category_code_LT01_1_count  0.44979    0.08276   5.435 8.64e-08 ***
## category_code_LT01_2_count  0.84624    0.07032  12.033  < 2e-16 ***
## category_code_LT01_5_count  1.00976    0.06173  16.357  < 2e-16 ***
## category_code_LT01_8_count -0.12979    0.27564  -0.471    0.638    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.618 
## F-statistic:   202 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count 0.620359367725214 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0149 -0.8033  0.0279  0.9105  3.4526 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94052    0.08804 112.912  < 2e-16 ***
## category_code_LT01_1_count  0.43707    0.08267   5.287 1.87e-07 ***
## category_code_LT01_2_count  0.81740    0.07188  11.372  < 2e-16 ***
## category_code_LT01_5_count  0.99475    0.06103  16.299  < 2e-16 ***
## category_code_LT01_9_count  0.41175    0.22603   1.822   0.0691 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 493 degrees of freedom
## Multiple R-squared:  0.6234, Adjusted R-squared:  0.6204 
## F-statistic:   204 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count 0.619379102047929 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9893 -0.7914  0.0220  0.8954  3.4837 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90942    0.09143 108.383  < 2e-16 ***
## category_code_LT01_1_count   0.44719    0.08255   5.417 9.47e-08 ***
## category_code_LT01_2_count   0.82621    0.07159  11.541  < 2e-16 ***
## category_code_LT01_5_count   1.00268    0.06087  16.473  < 2e-16 ***
## category_code_LT01_10_count  0.16059    0.11243   1.428    0.154    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 493 degrees of freedom
## Multiple R-squared:  0.6224, Adjusted R-squared:  0.6194 
## F-statistic: 203.2 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count 0.625485913986026 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0255 -0.7622  0.0453  0.8829  3.4352 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95792    0.08753 113.772  < 2e-16 ***
## category_code_LT01_1_count   0.37372    0.08517   4.388 1.40e-05 ***
## category_code_LT01_2_count   0.68314    0.08649   7.898 1.86e-14 ***
## category_code_LT01_5_count   0.98498    0.06068  16.231  < 2e-16 ***
## category_code_LT01_11_count  0.36651    0.11526   3.180  0.00157 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 493 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.6255 
## F-statistic: 208.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count 0.617804076230663 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0258 -0.7994  0.0040  0.8833  3.4490 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.944194   0.088312 112.603  < 2e-16 ***
## category_code_LT01_1_count   0.448349   0.083545   5.367 1.24e-07 ***
## category_code_LT01_2_count   0.846446   0.071841  11.782  < 2e-16 ***
## category_code_LT01_5_count   1.005220   0.061345  16.386  < 2e-16 ***
## category_code_LT01_12_count -0.001925   0.208947  -0.009    0.993    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.6178 
## F-statistic: 201.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count 0.617819149959011 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0257 -0.7980  0.0046  0.8856  3.4488 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94434    0.08831 112.601  < 2e-16 ***
## category_code_LT01_1_count   0.44633    0.08383   5.324 1.54e-07 ***
## category_code_LT01_2_count   0.84555    0.07055  11.985  < 2e-16 ***
## category_code_LT01_5_count   1.00479    0.06102  16.466  < 2e-16 ***
## category_code_LT01_13_count  0.03449    0.24683   0.140    0.889    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.6178 
## F-statistic: 201.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_14_count 0.617921715282845 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0255 -0.7941  0.0063  0.8888  3.4471 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94606    0.08843 112.479  < 2e-16 ***
## category_code_LT01_1_count   0.44364    0.08354   5.311 1.66e-07 ***
## category_code_LT01_2_count   0.84275    0.07092  11.883  < 2e-16 ***
## category_code_LT01_5_count   1.00210    0.06146  16.305  < 2e-16 ***
## category_code_LT01_14_count  0.12844    0.32958   0.390    0.697    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6179 
## F-statistic: 201.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_15_count 0.617907159980514 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0251 -0.8012  0.0129  0.8800  3.4497 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94348    0.08832 112.584  < 2e-16 ***
## category_code_LT01_1_count   0.45412    0.08426   5.390  1.1e-07 ***
## category_code_LT01_2_count   0.84824    0.07053  12.027  < 2e-16 ***
## category_code_LT01_5_count   1.00511    0.06096  16.488  < 2e-16 ***
## category_code_LT01_15_count -0.27920    0.76532  -0.365    0.715    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6179 
## F-statistic: 201.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_16_count 0.61787637712049 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0258 -0.7974  0.0065  0.8898  3.4487 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94444    0.08831 112.614  < 2e-16 ***
## category_code_LT01_1_count   0.44919    0.08277   5.427 8.99e-08 ***
## category_code_LT01_2_count   0.84332    0.07101  11.876  < 2e-16 ***
## category_code_LT01_5_count   1.00483    0.06097  16.480  < 2e-16 ***
## category_code_LT01_16_count  0.35966    1.17707   0.306     0.76    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6179 
## F-statistic: 201.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count 0.624666988359471 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0011 -0.7585  0.0318  0.8570  3.4375 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96522    0.08731 114.141  < 2e-16 ***
## category_code_LT01_1_count  0.27196    0.08888   3.060  0.00234 ** 
## category_code_LT01_3_count  0.34041    0.11284   3.017  0.00269 ** 
## category_code_LT01_4_count  0.81205    0.08913   9.111  < 2e-16 ***
## category_code_LT01_5_count  0.93918    0.06183  15.190  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 493 degrees of freedom
## Multiple R-squared:  0.6277, Adjusted R-squared:  0.6247 
## F-statistic: 207.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 0.625102553305449 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9932 -0.7669  0.0515  0.9425  3.8838 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96101    0.08733 114.066  < 2e-16 ***
## category_code_LT01_1_count  0.28429    0.08834   3.218  0.00137 ** 
## category_code_LT01_4_count  0.84735    0.08362  10.133  < 2e-16 ***
## category_code_LT01_5_count  0.93389    0.06196  15.072  < 2e-16 ***
## category_code_LT01_6_count  0.46572    0.14966   3.112  0.00197 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 493 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6251 
## F-statistic: 208.2 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 0.625150179410957 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0196 -0.7695  0.0167  0.8686  3.8662 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97992    0.08714 114.528  < 2e-16 ***
## category_code_LT01_1_count  0.28246    0.08838   3.196  0.00148 ** 
## category_code_LT01_4_count  0.85218    0.08302  10.264  < 2e-16 ***
## category_code_LT01_5_count  0.94461    0.06163  15.328  < 2e-16 ***
## category_code_LT01_7_count  0.47917    0.15347   3.122  0.00190 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 493 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6252 
## F-statistic: 208.2 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 0.617997295042587 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0325 -0.7532 -0.0058  0.9254  3.8465 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97999    0.08800 113.409  < 2e-16 ***
## category_code_LT01_1_count  0.31079    0.08885   3.498 0.000511 ***
## category_code_LT01_4_count  0.94389    0.07843  12.035  < 2e-16 ***
## category_code_LT01_5_count  0.96313    0.06281  15.334  < 2e-16 ***
## category_code_LT01_8_count -0.15928    0.27564  -0.578 0.563628    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.618 
## F-statistic:   202 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 0.621548448062337 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0123 -0.7891  0.0311  0.9200  3.8636 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97205    0.08760 113.830  < 2e-16 ***
## category_code_LT01_1_count  0.29748    0.08855   3.360 0.000841 ***
## category_code_LT01_4_count  0.91048    0.07946  11.458  < 2e-16 ***
## category_code_LT01_5_count  0.94546    0.06202  15.244  < 2e-16 ***
## category_code_LT01_9_count  0.49916    0.22406   2.228 0.026345 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 493 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:  0.6215 
## F-statistic: 205.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 0.619753369105945 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9855 -0.7759  0.0341  0.9115  3.6896 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93823    0.09124 108.918  < 2e-16 ***
## category_code_LT01_1_count   0.31038    0.08860   3.503 0.000502 ***
## category_code_LT01_4_count   0.92031    0.07956  11.567  < 2e-16 ***
## category_code_LT01_5_count   0.95557    0.06194  15.427  < 2e-16 ***
## category_code_LT01_10_count  0.18107    0.11203   1.616 0.106681    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 493 degrees of freedom
## Multiple R-squared:  0.6228, Adjusted R-squared:  0.6198 
## F-statistic: 203.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 0.628107258451039 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0225 -0.7644  0.0251  0.9054  3.6018 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98492    0.08681 115.020  < 2e-16 ***
## category_code_LT01_1_count   0.24613    0.08925   2.758 0.006038 ** 
## category_code_LT01_4_count   0.75455    0.09267   8.142  3.2e-15 ***
## category_code_LT01_5_count   0.94161    0.06140  15.337  < 2e-16 ***
## category_code_LT01_11_count  0.41051    0.11073   3.707 0.000233 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 493 degrees of freedom
## Multiple R-squared:  0.6311, Adjusted R-squared:  0.6281 
## F-statistic: 210.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 0.617977971708148 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0243 -0.7678  0.0029  0.9351  3.8538 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97827    0.08797 113.429  < 2e-16 ***
## category_code_LT01_1_count   0.30266    0.08957   3.379 0.000785 ***
## category_code_LT01_4_count   0.93666    0.07942  11.794  < 2e-16 ***
## category_code_LT01_5_count   0.95378    0.06245  15.273  < 2e-16 ***
## category_code_LT01_12_count  0.11512    0.20710   0.556 0.578572    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.618 
## F-statistic:   202 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 0.617745380398712 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0271 -0.7682 -0.0063  0.9178  3.8498 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97865    0.08800 113.396  < 2e-16 ***
## category_code_LT01_1_count   0.30797    0.08972   3.433 0.000648 ***
## category_code_LT01_4_count   0.94299    0.07871  11.980  < 2e-16 ***
## category_code_LT01_5_count   0.95737    0.06213  15.408  < 2e-16 ***
## category_code_LT01_13_count  0.02316    0.24693   0.094 0.925323    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6177 
## F-statistic: 201.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 0.617744963194073 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0272 -0.7686 -0.0047  0.9315  3.8492 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97900    0.08812 113.248  < 2e-16 ***
## category_code_LT01_1_count   0.30832    0.08929   3.453 0.000602 ***
## category_code_LT01_4_count   0.94248    0.07940  11.871  < 2e-16 ***
## category_code_LT01_5_count   0.95695    0.06247  15.318  < 2e-16 ***
## category_code_LT01_14_count  0.03006    0.33083   0.091 0.927637    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6177 
## F-statistic: 201.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 0.617763567980324 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0269 -0.7678 -0.0060  0.9317  3.8473 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97829    0.08801 113.380  < 2e-16 ***
## category_code_LT01_1_count   0.31202    0.09026   3.457 0.000594 ***
## category_code_LT01_4_count   0.94443    0.07859  12.017  < 2e-16 ***
## category_code_LT01_5_count   0.95755    0.06209  15.422  < 2e-16 ***
## category_code_LT01_15_count -0.13733    0.76467  -0.180 0.857548    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6178 
## F-statistic: 201.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 0.618731033324284 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0255 -0.7679  0.0019  0.9334  3.8483 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97836    0.08788 113.544  < 2e-16 ***
## category_code_LT01_1_count   0.31048    0.08873   3.499 0.000509 ***
## category_code_LT01_4_count   0.93744    0.07854  11.936  < 2e-16 ***
## category_code_LT01_5_count   0.95548    0.06204  15.401  < 2e-16 ***
## category_code_LT01_16_count  1.32240    1.16733   1.133 0.257834    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 493 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6187 
## F-statistic: 202.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count 0.640748714538151 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9672 -0.7337  0.0660  0.8725  3.4828 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95072    0.08529 116.667  < 2e-16 ***
## category_code_LT01_2_count  0.50415    0.08933   5.644 2.81e-08 ***
## category_code_LT01_3_count  0.24014    0.11244   2.136   0.0332 *  
## category_code_LT01_4_count  0.61540    0.09640   6.384 4.00e-10 ***
## category_code_LT01_5_count  0.91118    0.06038  15.092  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 493 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:  0.6407 
## F-statistic: 222.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count 0.617549420444578 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0009 -0.7635  0.0221  0.8876  3.8408 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96019    0.08806 113.109  < 2e-16 ***
## category_code_LT01_2_count  0.74787    0.08084   9.251  < 2e-16 ***
## category_code_LT01_3_count  0.45060    0.10956   4.113 4.58e-05 ***
## category_code_LT01_5_count  0.94617    0.06209  15.239  < 2e-16 ***
## category_code_LT01_6_count  0.44264    0.15298   2.893  0.00398 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 493 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.6175 
## F-statistic: 201.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count 0.622738476965924 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0165 -0.7578 -0.0179  0.8373  3.8267 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97427    0.08732 114.227  < 2e-16 ***
## category_code_LT01_2_count  0.73835    0.07862   9.392  < 2e-16 ***
## category_code_LT01_3_count  0.44634    0.10849   4.114 4.55e-05 ***
## category_code_LT01_5_count  0.94835    0.06140  15.446  < 2e-16 ***
## category_code_LT01_7_count  0.58876    0.15067   3.907 0.000106 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 493 degrees of freedom
## Multiple R-squared:  0.6258, Adjusted R-squared:  0.6227 
## F-statistic: 206.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count 0.611175458619494 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0346 -0.7652  0.0074  0.8621  3.8253 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97563    0.08869 112.475  < 2e-16 ***
## category_code_LT01_2_count  0.83279    0.07594  10.966  < 2e-16 ***
## category_code_LT01_3_count  0.49459    0.10951   4.516 7.88e-06 ***
## category_code_LT01_5_count  0.97251    0.06285  15.474  < 2e-16 ***
## category_code_LT01_8_count -0.10880    0.27799  -0.391    0.696    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 493 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6112 
## F-statistic: 196.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count 0.612877045290232 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0231 -0.7631  0.0227  0.8829  3.8294 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97155    0.08848 112.704  < 2e-16 ***
## category_code_LT01_2_count  0.81458    0.07672  10.617  < 2e-16 ***
## category_code_LT01_3_count  0.46744    0.11053   4.229  2.8e-05 ***
## category_code_LT01_5_count  0.96188    0.06214  15.480  < 2e-16 ***
## category_code_LT01_9_count  0.35092    0.23035   1.523    0.128    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 493 degrees of freedom
## Multiple R-squared:  0.616,  Adjusted R-squared:  0.6129 
## F-statistic: 197.7 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count 0.611391518619168 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0151 -0.7522  0.0109  0.8401  3.8422 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95880    0.09184 108.441  < 2e-16 ***
## category_code_LT01_2_count   0.82842    0.07622  10.868  < 2e-16 ***
## category_code_LT01_3_count   0.48007    0.11128   4.314 1.94e-05 ***
## category_code_LT01_5_count   0.96863    0.06209  15.600  < 2e-16 ***
## category_code_LT01_10_count  0.07552    0.11552   0.654    0.514    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 493 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6114 
## F-statistic: 196.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count 0.619641821156081 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0323 -0.7735 -0.0100  0.8269  4.0630 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98499    0.08773 113.811  < 2e-16 ***
## category_code_LT01_2_count   0.67116    0.08939   7.508 2.83e-13 ***
## category_code_LT01_3_count   0.38218    0.11327   3.374 0.000799 ***
## category_code_LT01_5_count   0.95563    0.06155  15.525  < 2e-16 ***
## category_code_LT01_11_count  0.38978    0.11683   3.336 0.000913 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 493 degrees of freedom
## Multiple R-squared:  0.6227, Adjusted R-squared:  0.6196 
## F-statistic: 203.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count 0.611171891459006 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0290 -0.7639 -0.0059  0.8705  3.8266 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97432    0.08865 112.513  < 2e-16 ***
## category_code_LT01_2_count   0.82671    0.07759  10.654  < 2e-16 ***
## category_code_LT01_3_count   0.48988    0.10982   4.461 1.01e-05 ***
## category_code_LT01_5_count   0.96636    0.06241  15.483  < 2e-16 ***
## category_code_LT01_12_count  0.08071    0.20934   0.386      0.7    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 493 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6112 
## F-statistic: 196.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count 0.611578479258562 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0292 -0.7714  0.0069  0.8910  3.8268 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97417    0.08860 112.571  < 2e-16 ***
## category_code_LT01_2_count   0.82547    0.07644  10.799  < 2e-16 ***
## category_code_LT01_3_count   0.48936    0.10951   4.469 9.77e-06 ***
## category_code_LT01_5_count   0.96686    0.06212  15.565  < 2e-16 ***
## category_code_LT01_13_count  0.20039    0.24575   0.815    0.415    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 493 degrees of freedom
## Multiple R-squared:  0.6147, Adjusted R-squared:  0.6116 
## F-statistic: 196.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count 0.61208413860337 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0284 -0.7679  0.0159  0.8542  3.8226 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97831    0.08861 112.615  < 2e-16 ***
## category_code_LT01_2_count   0.81693    0.07712  10.593  < 2e-16 ***
## category_code_LT01_3_count   0.49332    0.10933   4.512 8.03e-06 ***
## category_code_LT01_5_count   0.95971    0.06254  15.347  < 2e-16 ***
## category_code_LT01_14_count  0.37605    0.32876   1.144    0.253    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 493 degrees of freedom
## Multiple R-squared:  0.6152, Adjusted R-squared:  0.6121 
## F-statistic: 197.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_15_count 0.611055446491905 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0310 -0.7641  0.0094  0.8701  3.8264 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97456    0.08866 112.497  < 2e-16 ***
## category_code_LT01_2_count   0.83267    0.07616  10.933  < 2e-16 ***
## category_code_LT01_3_count   0.49278    0.11060   4.455 1.04e-05 ***
## category_code_LT01_5_count   0.96879    0.06213  15.593  < 2e-16 ***
## category_code_LT01_15_count  0.02436    0.76568   0.032    0.975    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 493 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6111 
## F-statistic: 196.2 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_16_count 0.611113055008319 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0305 -0.7636  0.0073  0.8659  3.8269 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97409    0.08867 112.485  < 2e-16 ***
## category_code_LT01_2_count   0.83421    0.07612  10.960  < 2e-16 ***
## category_code_LT01_3_count   0.49575    0.10984   4.513 7.99e-06 ***
## category_code_LT01_5_count   0.96884    0.06211  15.598  < 2e-16 ***
## category_code_LT01_16_count -0.32399    1.19065  -0.272    0.786    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 493 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6111 
## F-statistic: 196.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 0.640487850103678 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9638 -0.7384  0.0859  0.8953  3.4875 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94949    0.08536 116.561  < 2e-16 ***
## category_code_LT01_2_count  0.50519    0.08945   5.648 2.75e-08 ***
## category_code_LT01_4_count  0.64875    0.09225   7.032 6.82e-12 ***
## category_code_LT01_5_count  0.90804    0.06056  14.995  < 2e-16 ***
## category_code_LT01_6_count  0.30792    0.15025   2.049    0.041 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 493 degrees of freedom
## Multiple R-squared:  0.6434, Adjusted R-squared:  0.6405 
## F-statistic: 222.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 0.642535553510534 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9781 -0.7037  0.0603  0.8606  3.4713 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96058    0.08500 117.181  < 2e-16 ***
## category_code_LT01_2_count  0.51558    0.08754   5.890 7.17e-09 ***
## category_code_LT01_4_count  0.62527    0.09304   6.721 5.01e-11 ***
## category_code_LT01_5_count  0.91268    0.06013  15.178  < 2e-16 ***
## category_code_LT01_7_count  0.40011    0.15071   2.655  0.00819 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 493 degrees of freedom
## Multiple R-squared:  0.6454, Adjusted R-squared:  0.6425 
## F-statistic: 224.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 0.63757336766471 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9861 -0.7494  0.0489  0.8432  3.4581 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95988    0.08563 116.313  < 2e-16 ***
## category_code_LT01_2_count  0.54851    0.08725   6.287 7.14e-10 ***
## category_code_LT01_4_count  0.68901    0.09063   7.602 1.48e-13 ***
## category_code_LT01_5_count  0.92531    0.06117  15.128  < 2e-16 ***
## category_code_LT01_8_count -0.12056    0.26835  -0.449    0.653    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 493 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6376 
## F-statistic: 219.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 0.639340285031251 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9732 -0.7487  0.0572  0.8712  3.4757 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95503    0.08541 116.560  < 2e-16 ***
## category_code_LT01_2_count  0.52866    0.08791   6.014 3.54e-09 ***
## category_code_LT01_4_count  0.67517    0.09073   7.441 4.47e-13 ***
## category_code_LT01_5_count  0.91369    0.06049  15.105  < 2e-16 ***
## category_code_LT01_9_count  0.35686    0.22055   1.618    0.106    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 493 degrees of freedom
## Multiple R-squared:  0.6422, Adjusted R-squared:  0.6393 
## F-statistic: 221.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 0.638097524764369 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9590 -0.7673  0.0662  0.8524  3.3717 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93616    0.08869 112.029  < 2e-16 ***
## category_code_LT01_2_count   0.53971    0.08769   6.155 1.56e-09 ***
## category_code_LT01_4_count   0.68161    0.09079   7.508 2.84e-13 ***
## category_code_LT01_5_count   0.92033    0.06042  15.231  < 2e-16 ***
## category_code_LT01_10_count  0.10522    0.10992   0.957    0.339    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 493 degrees of freedom
## Multiple R-squared:  0.641,  Adjusted R-squared:  0.6381 
## F-statistic: 220.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 0.640533600777387 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9861 -0.7534  0.0815  0.8560  3.4616 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96586    0.08531 116.822  < 2e-16 ***
## category_code_LT01_2_count   0.47181    0.09453   4.991 8.35e-07 ***
## category_code_LT01_4_count   0.61656    0.09665   6.380 4.09e-10 ***
## category_code_LT01_5_count   0.91665    0.06025  15.213  < 2e-16 ***
## category_code_LT01_11_count  0.24007    0.11627   2.065   0.0395 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 493 degrees of freedom
## Multiple R-squared:  0.6434, Adjusted R-squared:  0.6405 
## F-statistic: 222.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 0.637431961292688 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9816 -0.7482  0.0466  0.8467  3.4646 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95860    0.08560 116.332  < 2e-16 ***
## category_code_LT01_2_count   0.54742    0.08824   6.204 1.17e-09 ***
## category_code_LT01_4_count   0.68722    0.09099   7.553 2.08e-13 ***
## category_code_LT01_5_count   0.92061    0.06073  15.158  < 2e-16 ***
## category_code_LT01_12_count  0.01969    0.20229   0.097    0.922    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 493 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.6374 
## F-statistic: 219.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 0.637486628552587 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9817 -0.7482  0.0436  0.8455  3.4644 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95861    0.08560 116.343  < 2e-16 ***
## category_code_LT01_2_count   0.54746    0.08736   6.267 8.05e-10 ***
## category_code_LT01_4_count   0.68537    0.09108   7.525 2.52e-13 ***
## category_code_LT01_5_count   0.92073    0.06049  15.222  < 2e-16 ***
## category_code_LT01_13_count  0.06902    0.23838   0.290    0.772    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 493 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.6375 
## F-statistic: 219.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 0.637435786244791 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9820 -0.7487  0.0463  0.8365  3.4642 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95913    0.08570 116.215  < 2e-16 ***
## category_code_LT01_2_count   0.54813    0.08739   6.273 7.78e-10 ***
## category_code_LT01_4_count   0.68646    0.09152   7.500 2.99e-13 ***
## category_code_LT01_5_count   0.92042    0.06078  15.144  < 2e-16 ***
## category_code_LT01_14_count  0.03889    0.32099   0.121    0.904    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 493 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.6374 
## F-statistic: 219.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 0.637425849080165 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9821 -0.7482  0.0412  0.8470  3.4639 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95866    0.08561 116.332  < 2e-16 ***
## category_code_LT01_2_count   0.54849    0.08746   6.272 7.82e-10 ***
## category_code_LT01_4_count   0.68774    0.09097   7.560 1.98e-13 ***
## category_code_LT01_5_count   0.92119    0.06048  15.231  < 2e-16 ***
## category_code_LT01_15_count  0.02507    0.73455   0.034    0.973    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 493 degrees of freedom
## Multiple R-squared:  0.6403, Adjusted R-squared:  0.6374 
## F-statistic: 219.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 0.637524002009119 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9820 -0.7486  0.0407  0.8447  3.4641 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95900    0.08560 116.346  < 2e-16 ***
## category_code_LT01_2_count   0.54485    0.08788   6.200 1.20e-09 ***
## category_code_LT01_4_count   0.68916    0.09067   7.601 1.49e-13 ***
## category_code_LT01_5_count   0.92063    0.06048  15.222  < 2e-16 ***
## category_code_LT01_16_count  0.42064    1.14628   0.367    0.714    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 493 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.6375 
## F-statistic: 219.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 0.618292931084458 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0231 -0.7775 -0.0325  0.9758  3.8229 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97807    0.08784 113.592  < 2e-16 ***
## category_code_LT01_2_count  0.79016    0.07610  10.383  < 2e-16 ***
## category_code_LT01_5_count  0.95244    0.06185  15.400  < 2e-16 ***
## category_code_LT01_6_count  0.50238    0.15156   3.315 0.000984 ***
## category_code_LT01_7_count  0.63794    0.15074   4.232 2.76e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 493 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6183 
## F-statistic: 202.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 0.604559837844542 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0460 -0.8035 -0.0030  0.9701  3.8198 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.98114    0.08945 111.586  < 2e-16 ***
## category_code_LT01_2_count  0.90678    0.07219  12.562  < 2e-16 ***
## category_code_LT01_5_count  0.98103    0.06339  15.475  < 2e-16 ***
## category_code_LT01_6_count  0.53024    0.15430   3.436 0.000639 ***
## category_code_LT01_8_count -0.11445    0.28051  -0.408 0.683434    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 493 degrees of freedom
## Multiple R-squared:  0.6077, Adjusted R-squared:  0.6046 
## F-statistic:   191 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 0.607566075884537 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0300 -0.8386  0.0063  0.9785  3.8259 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97510    0.08910 111.953  < 2e-16 ***
## category_code_LT01_2_count  0.87402    0.07380  11.844  < 2e-16 ***
## category_code_LT01_5_count  0.96657    0.06266  15.427  < 2e-16 ***
## category_code_LT01_6_count  0.50949    0.15382   3.312 0.000993 ***
## category_code_LT01_9_count  0.45594    0.22957   1.986 0.047581 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.411 on 493 degrees of freedom
## Multiple R-squared:  0.6107, Adjusted R-squared:  0.6076 
## F-statistic: 193.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 0.605090485727374 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0199 -0.8068 -0.0173  0.9680  3.8430 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95792    0.09259 107.552  < 2e-16 ***
## category_code_LT01_2_count   0.89871    0.07270  12.362  < 2e-16 ***
## category_code_LT01_5_count   0.97684    0.06263  15.598  < 2e-16 ***
## category_code_LT01_6_count   0.50448    0.15607   3.232  0.00131 ** 
## category_code_LT01_10_count  0.10565    0.11603   0.911  0.36296    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 493 degrees of freedom
## Multiple R-squared:  0.6083, Adjusted R-squared:  0.6051 
## F-statistic: 191.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 0.616659580847878 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0384 -0.8269  0.0291  0.9351  3.8490 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98953    0.08806 113.439  < 2e-16 ***
## category_code_LT01_2_count   0.69312    0.08920   7.770 4.59e-14 ***
## category_code_LT01_5_count   0.95791    0.06189  15.477  < 2e-16 ***
## category_code_LT01_6_count   0.42097    0.15412   2.732  0.00653 ** 
## category_code_LT01_11_count  0.45156    0.11384   3.966 8.38e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 493 degrees of freedom
## Multiple R-squared:  0.6197, Adjusted R-squared:  0.6167 
## F-statistic: 200.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 0.604525115297386 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0406 -0.8243 -0.0268  0.9652  3.8211 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97990    0.08941 111.618  < 2e-16 ***
## category_code_LT01_2_count   0.90149    0.07385  12.208  < 2e-16 ***
## category_code_LT01_5_count   0.97505    0.06295  15.489  < 2e-16 ***
## category_code_LT01_6_count   0.52113    0.15517   3.358 0.000844 ***
## category_code_LT01_12_count  0.07435    0.21183   0.351 0.725758    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 493 degrees of freedom
## Multiple R-squared:  0.6077, Adjusted R-squared:  0.6045 
## F-statistic: 190.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 0.605232901186465 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0396 -0.8179 -0.0255  0.9730  3.8216 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97933    0.08933 111.709  < 2e-16 ***
## category_code_LT01_2_count   0.89589    0.07296  12.279  < 2e-16 ***
## category_code_LT01_5_count   0.97440    0.06267  15.547  < 2e-16 ***
## category_code_LT01_6_count   0.52733    0.15401   3.424 0.000668 ***
## category_code_LT01_13_count  0.24842    0.24751   1.004 0.316040    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 493 degrees of freedom
## Multiple R-squared:  0.6084, Adjusted R-squared:  0.6052 
## F-statistic: 191.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 0.60594372558056 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0380 -0.8234  0.0011  0.9437  3.8169 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98407    0.08930 111.806  < 2e-16 ***
## category_code_LT01_2_count   0.88416    0.07393  11.959  < 2e-16 ***
## category_code_LT01_5_count   0.96526    0.06315  15.285  < 2e-16 ***
## category_code_LT01_6_count   0.54230    0.15425   3.516 0.000479 ***
## category_code_LT01_14_count  0.45768    0.33217   1.378 0.168879    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.414 on 493 degrees of freedom
## Multiple R-squared:  0.6091, Adjusted R-squared:  0.6059 
## F-statistic: 192.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 0.604604720187118 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0425 -0.8158 -0.0325  0.9713  3.8208 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98017    0.08940 111.632  < 2e-16 ***
## category_code_LT01_2_count   0.90233    0.07284  12.387  < 2e-16 ***
## category_code_LT01_5_count   0.97739    0.06267  15.596  < 2e-16 ***
## category_code_LT01_6_count   0.52318    0.15439   3.389 0.000758 ***
## category_code_LT01_15_count  0.36101    0.76541   0.472 0.637378    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 493 degrees of freedom
## Multiple R-squared:  0.6078, Adjusted R-squared:  0.6046 
## F-statistic:   191 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 0.604578516090604 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0419 -0.8257 -0.0219  0.9715  3.8206 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98031    0.08941 111.628  < 2e-16 ***
## category_code_LT01_2_count   0.90164    0.07320  12.317  < 2e-16 ***
## category_code_LT01_5_count   0.97627    0.06270  15.571  < 2e-16 ***
## category_code_LT01_6_count   0.53394    0.15488   3.448 0.000614 ***
## category_code_LT01_16_count  0.52375    1.20227   0.436 0.663292    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 493 degrees of freedom
## Multiple R-squared:  0.6078, Adjusted R-squared:  0.6046 
## F-statistic:   191 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 0.609923880574989 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0657 -0.7875 -0.0193  0.9348  3.8030 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.99798    0.08867 112.761  < 2e-16 ***
## category_code_LT01_2_count  0.90208    0.06895  13.084  < 2e-16 ***
## category_code_LT01_5_count  0.98518    0.06266  15.724  < 2e-16 ***
## category_code_LT01_7_count  0.65984    0.15238   4.330 1.81e-05 ***
## category_code_LT01_8_count -0.11661    0.27851  -0.419    0.676    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 493 degrees of freedom
## Multiple R-squared:  0.6131, Adjusted R-squared:  0.6099 
## F-statistic: 195.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 0.612132220965896 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0508 -0.7856  0.0036  0.9537  3.8089 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.99201    0.08841 113.022  < 2e-16 ***
## category_code_LT01_2_count  0.87550    0.07045  12.427  < 2e-16 ***
## category_code_LT01_5_count  0.97226    0.06194  15.696  < 2e-16 ***
## category_code_LT01_7_count  0.62816    0.15278   4.112  4.6e-05 ***
## category_code_LT01_9_count  0.39596    0.22925   1.727   0.0848 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 493 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6121 
## F-statistic: 197.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 0.610702142152402 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0341 -0.7942  0.0093  0.9285  3.8309 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97007    0.09192 108.461  < 2e-16 ***
## category_code_LT01_2_count   0.88916    0.06991  12.718  < 2e-16 ***
## category_code_LT01_5_count   0.97984    0.06186  15.841  < 2e-16 ***
## category_code_LT01_7_count   0.64266    0.15273   4.208 3.06e-05 ***
## category_code_LT01_10_count  0.12302    0.11416   1.078    0.282    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 493 degrees of freedom
## Multiple R-squared:  0.6138, Adjusted R-squared:  0.6107 
## F-statistic: 195.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 0.618706795240544 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0562 -0.7628  0.0170  0.9215  3.7986 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00232    0.08763 114.144  < 2e-16 ***
## category_code_LT01_2_count   0.72249    0.08627   8.375 5.77e-16 ***
## category_code_LT01_5_count   0.96515    0.06139  15.723  < 2e-16 ***
## category_code_LT01_7_count   0.50140    0.15740   3.186 0.001536 ** 
## category_code_LT01_11_count  0.39702    0.11689   3.396 0.000738 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 493 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6187 
## F-statistic: 202.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 0.610130601305114 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0579 -0.7856 -0.0215  0.9180  3.8049 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99609    0.08860 112.824  < 2e-16 ***
## category_code_LT01_2_count   0.88962    0.07145  12.451  < 2e-16 ***
## category_code_LT01_5_count   0.97668    0.06226  15.688  < 2e-16 ***
## category_code_LT01_7_count   0.65542    0.15226   4.305 2.02e-05 ***
## category_code_LT01_12_count  0.13811    0.20898   0.661    0.509    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 493 degrees of freedom
## Multiple R-squared:  0.6133, Adjusted R-squared:  0.6101 
## F-statistic: 195.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 0.609932472501276 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0609 -0.7711 -0.0095  0.9369  3.8045 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99648    0.08862 112.805  < 2e-16 ***
## category_code_LT01_2_count   0.89900    0.06931  12.971  < 2e-16 ***
## category_code_LT01_5_count   0.98033    0.06193  15.829  < 2e-16 ***
## category_code_LT01_7_count   0.64845    0.15367   4.220 2.91e-05 ***
## category_code_LT01_13_count  0.10713    0.24831   0.431    0.666    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 493 degrees of freedom
## Multiple R-squared:  0.6131, Adjusted R-squared:  0.6099 
## F-statistic: 195.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 0.610202938443773 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0605 -0.7888 -0.0056  0.9158  3.8017 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99921    0.08865 112.795  < 2e-16 ***
## category_code_LT01_2_count   0.89394    0.06982  12.803  < 2e-16 ***
## category_code_LT01_5_count   0.97580    0.06232  15.658  < 2e-16 ***
## category_code_LT01_7_count   0.64668    0.15293   4.229  2.8e-05 ***
## category_code_LT01_14_count  0.24067    0.33110   0.727    0.468    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 493 degrees of freedom
## Multiple R-squared:  0.6133, Adjusted R-squared:  0.6102 
## F-statistic: 195.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 0.610196305878174 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0616 -0.7697 -0.0170  0.9162  3.8042 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99671    0.08859 112.848  < 2e-16 ***
## category_code_LT01_2_count   0.89335    0.06997  12.767  < 2e-16 ***
## category_code_LT01_5_count   0.98110    0.06188  15.854  < 2e-16 ***
## category_code_LT01_7_count   0.65864    0.15223   4.327 1.83e-05 ***
## category_code_LT01_15_count  0.54714    0.75878   0.721    0.471    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 493 degrees of freedom
## Multiple R-squared:  0.6133, Adjusted R-squared:  0.6102 
## F-statistic: 195.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 0.609815330883235 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0618 -0.7781 -0.0142  0.9359  3.8040 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99698    0.08864 112.786  < 2e-16 ***
## category_code_LT01_2_count   0.90025    0.06957  12.939  < 2e-16 ***
## category_code_LT01_5_count   0.98090    0.06193  15.840  < 2e-16 ***
## category_code_LT01_7_count   0.65805    0.15233   4.320 1.89e-05 ***
## category_code_LT01_16_count  0.23200    1.18886   0.195    0.845    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 493 degrees of freedom
## Multiple R-squared:  0.613,  Adjusted R-squared:  0.6098 
## F-statistic: 195.2 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 0.610893225467014 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0719 -0.7746  0.0013  0.8944  4.2727 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00654    0.08856 112.987  < 2e-16 ***
## category_code_LT01_2_count   0.76182    0.08628   8.829  < 2e-16 ***
## category_code_LT01_5_count   0.98167    0.06264  15.673  < 2e-16 ***
## category_code_LT01_8_count  -0.05868    0.27798  -0.211    0.833    
## category_code_LT01_11_count  0.50545    0.11295   4.475  9.5e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 493 degrees of freedom
## Multiple R-squared:  0.614,  Adjusted R-squared:  0.6109 
## F-statistic: 196.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 0.613536496170723 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0576 -0.7901  0.0188  0.9067  4.3325 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00054    0.08826 113.306  < 2e-16 ***
## category_code_LT01_2_count   0.73597    0.08707   8.452 3.24e-16 ***
## category_code_LT01_5_count   0.96978    0.06186  15.677  < 2e-16 ***
## category_code_LT01_9_count   0.42173    0.22815   1.848   0.0651 .  
## category_code_LT01_11_count  0.48906    0.11292   4.331 1.80e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 493 degrees of freedom
## Multiple R-squared:  0.6166, Adjusted R-squared:  0.6135 
## F-statistic: 198.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 0.612023895437916 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0384 -0.7653  0.0175  0.8923  4.3328 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97575    0.09180 108.674  < 2e-16 ***
## category_code_LT01_2_count   0.74777    0.08687   8.608  < 2e-16 ***
## category_code_LT01_5_count   0.97786    0.06177  15.831  < 2e-16 ***
## category_code_LT01_10_count  0.13836    0.11368   1.217    0.224    
## category_code_LT01_11_count  0.49809    0.11295   4.410 1.27e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 493 degrees of freedom
## Multiple R-squared:  0.6151, Adjusted R-squared:  0.612 
## F-statistic:   197 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 0.610979625540094 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0718 -0.7695 -0.0065  0.8909  4.2699 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00647    0.08852 113.047  < 2e-16 ***
## category_code_LT01_2_count   0.76322    0.08637   8.836  < 2e-16 ***
## category_code_LT01_5_count   0.98171    0.06207  15.815  < 2e-16 ***
## category_code_LT01_11_count  0.51720    0.11669   4.432 1.15e-05 ***
## category_code_LT01_12_count -0.08464    0.21564  -0.393    0.695    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 493 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.611 
## F-statistic: 196.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 0.611211844091931 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0682 -0.7762  0.0054  0.8961  4.2836 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00538    0.08848 113.078  < 2e-16 ***
## category_code_LT01_2_count   0.75718    0.08647   8.757  < 2e-16 ***
## category_code_LT01_5_count   0.97809    0.06186  15.812  < 2e-16 ***
## category_code_LT01_11_count  0.49985    0.11323   4.414 1.25e-05 ***
## category_code_LT01_13_count  0.16501    0.24636   0.670    0.503    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 493 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6112 
## F-statistic: 196.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 0.611482692473015 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0680 -0.7595  0.0059  0.8894  4.2908 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00880    0.08851 113.086  < 2e-16 ***
## category_code_LT01_2_count   0.75205    0.08685   8.660  < 2e-16 ***
## category_code_LT01_5_count   0.97285    0.06226  15.627  < 2e-16 ***
## category_code_LT01_11_count  0.50000    0.11304   4.423  1.2e-05 ***
## category_code_LT01_14_count  0.29339    0.32954   0.890    0.374    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 493 degrees of freedom
## Multiple R-squared:  0.6146, Adjusted R-squared:  0.6115 
## F-statistic: 196.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 0.610955251297787 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0699 -0.7789 -0.0021  0.8904  4.2796 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00587    0.08851 113.051  < 2e-16 ***
## category_code_LT01_2_count   0.75884    0.08658   8.765  < 2e-16 ***
## category_code_LT01_5_count   0.97974    0.06184  15.843  < 2e-16 ***
## category_code_LT01_11_count  0.50281    0.11323   4.441 1.11e-05 ***
## category_code_LT01_15_count  0.26671    0.75996   0.351    0.726    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 493 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.611 
## F-statistic: 196.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 0.610884361611228 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0699 -0.7777 -0.0016  0.8931  4.2776 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00614    0.08852 113.033  < 2e-16 ***
## category_code_LT01_2_count   0.75968    0.08681   8.751  < 2e-16 ***
## category_code_LT01_5_count   0.97936    0.06185  15.833  < 2e-16 ***
## category_code_LT01_11_count  0.50605    0.11297   4.480  9.3e-06 ***
## category_code_LT01_16_count  0.21674    1.18715   0.183    0.855    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 493 degrees of freedom
## Multiple R-squared:  0.614,  Adjusted R-squared:  0.6109 
## F-statistic: 196.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 0.624500262149966 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9870 -0.7535  0.0057  0.9143  3.4654 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97475    0.08707 114.563  < 2e-16 ***
## category_code_LT01_3_count  0.34788    0.11257   3.090  0.00211 ** 
## category_code_LT01_4_count  0.84070    0.08567   9.813  < 2e-16 ***
## category_code_LT01_5_count  0.90516    0.06203  14.592  < 2e-16 ***
## category_code_LT01_6_count  0.45415    0.15023   3.023  0.00263 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 493 degrees of freedom
## Multiple R-squared:  0.6275, Adjusted R-squared:  0.6245 
## F-statistic: 207.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 0.625613193953221 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0102 -0.7634  0.0442  0.8601  3.4386 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.99188    0.08674 115.191  < 2e-16 ***
## category_code_LT01_3_count  0.36797    0.11179   3.292  0.00107 ** 
## category_code_LT01_4_count  0.82877    0.08609   9.626  < 2e-16 ***
## category_code_LT01_5_count  0.91392    0.06168  14.817  < 2e-16 ***
## category_code_LT01_7_count  0.49854    0.15290   3.261  0.00119 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 493 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6256 
## F-statistic: 208.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 0.617766168911161 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0236 -0.7835  0.0351  0.8594  3.4186 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.99389    0.08769 113.974   <2e-16 ***
## category_code_LT01_3_count  0.38962    0.11280   3.454   0.0006 ***
## category_code_LT01_4_count  0.92948    0.08126  11.438   <2e-16 ***
## category_code_LT01_5_count  0.93029    0.06293  14.784   <2e-16 ***
## category_code_LT01_8_count -0.14899    0.27564  -0.541   0.5891    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6178 
## F-statistic: 201.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 0.620320209839819 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0079 -0.7690  0.0467  0.8843  3.4397 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.98749    0.08739 114.284   <2e-16 ***
## category_code_LT01_3_count  0.35379    0.11386   3.107    0.002 ** 
## category_code_LT01_4_count  0.91053    0.08157  11.163   <2e-16 ***
## category_code_LT01_5_count  0.91689    0.06217  14.748   <2e-16 ***
## category_code_LT01_9_count  0.43121    0.22694   1.900    0.058 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 493 degrees of freedom
## Multiple R-squared:  0.6234, Adjusted R-squared:  0.6203 
## F-statistic:   204 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 0.618250332302444 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9952 -0.7588  0.0489  0.8718  3.3289 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96921    0.09089 109.680  < 2e-16 ***
## category_code_LT01_3_count   0.36783    0.11471   3.207  0.00143 ** 
## category_code_LT01_4_count   0.92435    0.08135  11.362  < 2e-16 ***
## category_code_LT01_5_count   0.92499    0.06219  14.875  < 2e-16 ***
## category_code_LT01_10_count  0.10945    0.11425   0.958  0.33853    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6183 
## F-statistic: 202.2 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 0.626864459377303 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0184 -0.7594  0.0457  0.8769  3.4289 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99741    0.08661 115.433  < 2e-16 ***
## category_code_LT01_3_count   0.28145    0.11551   2.437 0.015178 *  
## category_code_LT01_4_count   0.76289    0.09320   8.186 2.33e-15 ***
## category_code_LT01_5_count   0.91769    0.06152  14.918  < 2e-16 ***
## category_code_LT01_11_count  0.39618    0.11287   3.510 0.000489 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 493 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6269 
## F-statistic: 209.7 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 0.617933880705064 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0148 -0.7712  0.0356  0.8763  3.4311 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99153    0.08764 114.011  < 2e-16 ***
## category_code_LT01_3_count   0.38142    0.11316   3.371 0.000809 ***
## category_code_LT01_4_count   0.91898    0.08245  11.147  < 2e-16 ***
## category_code_LT01_5_count   0.92107    0.06248  14.741  < 2e-16 ***
## category_code_LT01_12_count  0.14700    0.20610   0.713 0.476045    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6179 
## F-statistic:   202 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 0.617741698237378 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0179 -0.7750  0.0368  0.8606  3.4267 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99224    0.08765 114.002  < 2e-16 ***
## category_code_LT01_3_count   0.38712    0.11280   3.432  0.00065 ***
## category_code_LT01_4_count   0.92306    0.08209  11.245  < 2e-16 ***
## category_code_LT01_5_count   0.92442    0.06225  14.851  < 2e-16 ***
## category_code_LT01_13_count  0.12483    0.24455   0.510  0.60995    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6177 
## F-statistic: 201.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 0.617800567462784 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0180 -0.7586  0.0375  0.8651  3.4279 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99444    0.08771 113.951  < 2e-16 ***
## category_code_LT01_3_count   0.39089    0.11286   3.464  0.00058 ***
## category_code_LT01_4_count   0.91815    0.08338  11.012  < 2e-16 ***
## category_code_LT01_5_count   0.92135    0.06258  14.723  < 2e-16 ***
## category_code_LT01_14_count  0.19107    0.32936   0.580  0.56209    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.6178 
## F-statistic: 201.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 0.617539775362402 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0186 -0.7812  0.0321  0.8610  3.4256 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.992460   0.087674 113.972  < 2e-16 ***
## category_code_LT01_3_count   0.388480   0.113798   3.414 0.000694 ***
## category_code_LT01_4_count   0.929075   0.081513  11.398  < 2e-16 ***
## category_code_LT01_5_count   0.925207   0.062263  14.860  < 2e-16 ***
## category_code_LT01_15_count -0.009412   0.759358  -0.012 0.990116    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 493 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.6175 
## F-statistic: 201.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 0.617875338283374 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0186 -0.7778  0.0305  0.8601  3.4260 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99291    0.08764 114.027  < 2e-16 ***
## category_code_LT01_3_count   0.37890    0.11366   3.334 0.000922 ***
## category_code_LT01_4_count   0.92994    0.08126  11.444  < 2e-16 ***
## category_code_LT01_5_count   0.92443    0.06223  14.856  < 2e-16 ***
## category_code_LT01_16_count  0.77514    1.17786   0.658 0.510788    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6179 
## F-statistic: 201.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 0.625915399477166 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0027 -0.7605  0.0062  0.9143  4.0530 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.98889    0.08676 115.129  < 2e-16 ***
## category_code_LT01_4_count  0.87073    0.07947  10.957  < 2e-16 ***
## category_code_LT01_5_count  0.90740    0.06184  14.673  < 2e-16 ***
## category_code_LT01_6_count  0.49932    0.14891   3.353 0.000861 ***
## category_code_LT01_7_count  0.51648    0.15263   3.384 0.000772 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 493 degrees of freedom
## Multiple R-squared:  0.6289, Adjusted R-squared:  0.6259 
## F-statistic: 208.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 0.617504785082986 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0178 -0.7812  0.0283  0.9147  4.0502 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.99165    0.08777 113.843  < 2e-16 ***
## category_code_LT01_4_count  0.98189    0.07322  13.410  < 2e-16 ***
## category_code_LT01_5_count  0.92519    0.06310  14.662  < 2e-16 ***
## category_code_LT01_6_count  0.51282    0.15067   3.404 0.000719 ***
## category_code_LT01_8_count -0.16516    0.27588  -0.599 0.549667    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 493 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.6175 
## F-statistic: 201.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 0.620900483142205 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9988 -0.7731  0.0324  0.9152  4.0584 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.98353    0.08739 114.236  < 2e-16 ***
## category_code_LT01_4_count  0.94878    0.07442  12.750  < 2e-16 ***
## category_code_LT01_5_count  0.90941    0.06233  14.591  < 2e-16 ***
## category_code_LT01_6_count  0.48523    0.15028   3.229  0.00133 ** 
## category_code_LT01_9_count  0.49063    0.22446   2.186  0.02930 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 493 degrees of freedom
## Multiple R-squared:  0.624,  Adjusted R-squared:  0.6209 
## F-statistic: 204.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 0.618037540995909 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9877 -0.7773 -0.0024  0.9041  3.9484 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96542    0.09094 109.580  < 2e-16 ***
## category_code_LT01_4_count   0.97314    0.07363  13.217  < 2e-16 ***
## category_code_LT01_5_count   0.91963    0.06238  14.742  < 2e-16 ***
## category_code_LT01_6_count   0.48279    0.15266   3.163  0.00166 ** 
## category_code_LT01_10_count  0.11655    0.11393   1.023  0.30681    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.618 
## F-statistic:   202 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 0.627693959844438 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0110 -0.7448  0.0137  0.9600  3.7617 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99429    0.08656 115.458  < 2e-16 ***
## category_code_LT01_4_count   0.78456    0.08954   8.762  < 2e-16 ***
## category_code_LT01_5_count   0.91155    0.06163  14.791  < 2e-16 ***
## category_code_LT01_6_count   0.40173    0.15131   2.655  0.00819 ** 
## category_code_LT01_11_count  0.41250    0.11080   3.723  0.00022 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 493 degrees of freedom
## Multiple R-squared:  0.6307, Adjusted R-squared:  0.6277 
## F-statistic: 210.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 0.617477911903527 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0098 -0.7863  0.0040  0.9485  4.0523 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98960    0.08774 113.855  < 2e-16 ***
## category_code_LT01_4_count   0.97368    0.07451  13.068  < 2e-16 ***
## category_code_LT01_5_count   0.91661    0.06266  14.628  < 2e-16 ***
## category_code_LT01_6_count   0.49806    0.15184   3.280  0.00111 ** 
## category_code_LT01_12_count  0.11791    0.20723   0.569  0.56962    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 493 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.6175 
## F-statistic: 201.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 0.617515952746894 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0114 -0.7793  0.0060  0.9264  4.0521 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98977    0.08773 113.866  < 2e-16 ***
## category_code_LT01_4_count   0.97362    0.07436  13.094  < 2e-16 ***
## category_code_LT01_5_count   0.91860    0.06245  14.709  < 2e-16 ***
## category_code_LT01_6_count   0.51011    0.15055   3.388  0.00076 ***
## category_code_LT01_13_count  0.14934    0.24458   0.611  0.54176    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 493 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.6175 
## F-statistic: 201.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 0.617651364690023 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0111 -0.7820  0.0141  0.9163  4.0495 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99241    0.08777 113.850  < 2e-16 ***
## category_code_LT01_4_count   0.96685    0.07585  12.748  < 2e-16 ***
## category_code_LT01_5_count   0.91441    0.06282  14.556  < 2e-16 ***
## category_code_LT01_6_count   0.51899    0.15109   3.435 0.000643 ***
## category_code_LT01_14_count  0.24449    0.33042   0.740 0.459675    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 493 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.6177 
## F-statistic: 201.7 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 0.617277413363697 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0128 -0.7798 -0.0026  0.9197  4.0517 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99020    0.08776 113.838  < 2e-16 ***
## category_code_LT01_4_count   0.97879    0.07402  13.223  < 2e-16 ***
## category_code_LT01_5_count   0.91998    0.06246  14.730  < 2e-16 ***
## category_code_LT01_6_count   0.50717    0.15082   3.363 0.000832 ***
## category_code_LT01_15_count  0.19273    0.75415   0.256 0.798400    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 493 degrees of freedom
## Multiple R-squared:  0.6204, Adjusted R-squared:  0.6173 
## F-statistic: 201.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 0.618524310003523 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0098 -0.7791 -0.0023  0.9463  4.0523 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98955    0.08762 114.016  < 2e-16 ***
## category_code_LT01_4_count   0.97249    0.07345  13.239  < 2e-16 ***
## category_code_LT01_5_count   0.91663    0.06239  14.693  < 2e-16 ***
## category_code_LT01_6_count   0.52116    0.15063   3.460 0.000587 ***
## category_code_LT01_16_count  1.51475    1.16972   1.295 0.195937    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 493 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.6185 
## F-statistic: 202.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 0.617641401930323 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0464 -0.7606  0.0050  0.8582  4.0297 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                10.01219    0.08751 114.405  < 2e-16 ***
## category_code_LT01_4_count  0.98574    0.07255  13.586  < 2e-16 ***
## category_code_LT01_5_count  0.93681    0.06281  14.916  < 2e-16 ***
## category_code_LT01_7_count  0.52946    0.15436   3.430 0.000654 ***
## category_code_LT01_8_count -0.15875    0.27577  -0.576 0.565092    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 493 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.6176 
## F-statistic: 201.7 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 0.620658842003962 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0270 -0.7906 -0.0273  0.8818  4.0384 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                10.00346    0.08719 114.725  < 2e-16 ***
## category_code_LT01_4_count  0.95657    0.07358  13.000  < 2e-16 ***
## category_code_LT01_5_count  0.92145    0.06204  14.851  < 2e-16 ***
## category_code_LT01_7_count  0.49146    0.15461   3.179  0.00157 ** 
## category_code_LT01_9_count  0.46478    0.22530   2.063  0.03964 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 493 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6207 
## F-statistic: 204.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 0.618670614239284 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0080 -0.7668  0.0217  0.8594  3.9039 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97841    0.09085 109.832  < 2e-16 ***
## category_code_LT01_4_count   0.97088    0.07330  13.245  < 2e-16 ***
## category_code_LT01_5_count   0.93018    0.06203  14.997  < 2e-16 ***
## category_code_LT01_7_count   0.50915    0.15466   3.292  0.00107 ** 
## category_code_LT01_10_count  0.14523    0.11262   1.290  0.19781    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 493 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6187 
## F-statistic: 202.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 0.626822133397584 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0346 -0.7443  0.0430  0.9295  3.7554 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01056    0.08642 115.842  < 2e-16 ***
## category_code_LT01_4_count   0.80246    0.08841   9.077  < 2e-16 ***
## category_code_LT01_5_count   0.92209    0.06141  15.016  < 2e-16 ***
## category_code_LT01_7_count   0.38260    0.15778   2.425 0.015667 *  
## category_code_LT01_11_count  0.39801    0.11272   3.531 0.000453 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 493 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6268 
## F-statistic: 209.7 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 0.618072545142376 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0353 -0.7808  0.0179  0.8722  4.0330 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00891    0.08744 114.465  < 2e-16 ***
## category_code_LT01_4_count   0.96861    0.07462  12.981  < 2e-16 ***
## category_code_LT01_5_count   0.92556    0.06238  14.838  < 2e-16 ***
## category_code_LT01_7_count   0.52396    0.15422   3.398 0.000735 ***
## category_code_LT01_12_count  0.19354    0.20535   0.943 0.346396    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6181 
## F-statistic: 202.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 0.61740774682873 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0409 -0.7552  0.0057  0.8412  4.0314 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01052    0.08750 114.406  < 2e-16 ***
## category_code_LT01_4_count   0.98372    0.07309  13.460  < 2e-16 ***
## category_code_LT01_5_count   0.93119    0.06213  14.987  < 2e-16 ***
## category_code_LT01_7_count   0.52338    0.15544   3.367 0.000819 ***
## category_code_LT01_13_count  0.04276    0.24637   0.174 0.862275    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 493 degrees of freedom
## Multiple R-squared:  0.6205, Adjusted R-squared:  0.6174 
## F-statistic: 201.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 0.617416495643803 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0410 -0.7695 -0.0022  0.8603  4.0305 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01135    0.08757 114.318  < 2e-16 ***
## category_code_LT01_4_count   0.98230    0.07398  13.278  < 2e-16 ***
## category_code_LT01_5_count   0.93015    0.06243  14.899  < 2e-16 ***
## category_code_LT01_7_count   0.52438    0.15471   3.390 0.000756 ***
## category_code_LT01_14_count  0.06716    0.33009   0.203 0.838850    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 493 degrees of freedom
## Multiple R-squared:  0.6205, Adjusted R-squared:  0.6174 
## F-statistic: 201.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 0.617598879860301 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0413 -0.7497 -0.0010  0.8605  4.0314 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01053    0.08748 114.436  < 2e-16 ***
## category_code_LT01_4_count   0.97814    0.07379  13.255  < 2e-16 ***
## category_code_LT01_5_count   0.93178    0.06211  15.002  < 2e-16 ***
## category_code_LT01_7_count   0.52862    0.15433   3.425 0.000666 ***
## category_code_LT01_15_count  0.39595    0.75293   0.526 0.599205    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 493 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.6176 
## F-statistic: 201.7 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 0.618276847570247 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0396 -0.7549  0.0007  0.8694  4.0313 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01054    0.08740 114.538  < 2e-16 ***
## category_code_LT01_4_count   0.98016    0.07264  13.493  < 2e-16 ***
## category_code_LT01_5_count   0.92938    0.06208  14.971  < 2e-16 ***
## category_code_LT01_7_count   0.52600    0.15415   3.412 0.000697 ***
## category_code_LT01_16_count  1.25391    1.16793   1.074 0.283520    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 493 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6183 
## F-statistic: 202.2 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 0.613116870437303 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0395 -0.7948  0.0132  0.9372  4.0366 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                10.00528    0.08810 113.571   <2e-16 ***
## category_code_LT01_4_count  1.05881    0.06697  15.811   <2e-16 ***
## category_code_LT01_5_count  0.93686    0.06327  14.807   <2e-16 ***
## category_code_LT01_8_count -0.15111    0.27741  -0.545   0.5862    
## category_code_LT01_9_count  0.54786    0.22628   2.421   0.0158 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 493 degrees of freedom
## Multiple R-squared:  0.6162, Adjusted R-squared:  0.6131 
## F-statistic: 197.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 0.61048408231915 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0154 -0.7861  0.0192  0.9238  3.8713 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97397    0.09183 108.610   <2e-16 ***
## category_code_LT01_4_count   1.07918    0.06635  16.265   <2e-16 ***
## category_code_LT01_5_count   0.94714    0.06330  14.962   <2e-16 ***
## category_code_LT01_8_count  -0.13851    0.27827  -0.498    0.619    
## category_code_LT01_10_count  0.17898    0.11342   1.578    0.115    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 493 degrees of freedom
## Multiple R-squared:  0.6136, Adjusted R-squared:  0.6105 
## F-statistic: 195.7 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 0.62248379784428 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0443 -0.7365  0.0248  0.9119  3.7048 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01277    0.08696 115.145  < 2e-16 ***
## category_code_LT01_4_count   0.84943    0.08693   9.772  < 2e-16 ***
## category_code_LT01_5_count   0.93290    0.06242  14.945  < 2e-16 ***
## category_code_LT01_8_count  -0.10521    0.27393  -0.384    0.701    
## category_code_LT01_11_count  0.46783    0.10954   4.271 2.34e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 493 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.6225 
## F-statistic: 205.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 0.609326008104904 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0502 -0.8014 -0.0004  0.9389  4.0300 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01188    0.08848 113.158   <2e-16 ***
## category_code_LT01_4_count   1.08292    0.06747  16.050   <2e-16 ***
## category_code_LT01_5_count   0.94277    0.06367  14.807   <2e-16 ***
## category_code_LT01_8_count  -0.13874    0.27879  -0.498    0.619    
## category_code_LT01_12_count  0.21002    0.20780   1.011    0.313    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 493 degrees of freedom
## Multiple R-squared:  0.6125, Adjusted R-squared:  0.6093 
## F-statistic: 194.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 0.608754824458646 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0549 -0.7740 -0.0127  0.9368  4.0287 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01322    0.08853 113.108   <2e-16 ***
## category_code_LT01_4_count   1.09441    0.06624  16.522   <2e-16 ***
## category_code_LT01_5_count   0.94759    0.06347  14.929   <2e-16 ***
## category_code_LT01_8_count  -0.11951    0.27927  -0.428    0.669    
## category_code_LT01_13_count  0.13578    0.24777   0.548    0.584    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 493 degrees of freedom
## Multiple R-squared:  0.6119, Adjusted R-squared:  0.6088 
## F-statistic: 194.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 0.608673650156129 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0559 -0.7955 -0.0124  0.9350  4.0266 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01527    0.08861 113.024   <2e-16 ***
## category_code_LT01_4_count   1.09398    0.06713  16.296   <2e-16 ***
## category_code_LT01_5_count   0.94599    0.06376  14.837   <2e-16 ***
## category_code_LT01_8_count  -0.13016    0.27887  -0.467    0.641    
## category_code_LT01_14_count  0.14819    0.33304   0.445    0.657    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 493 degrees of freedom
## Multiple R-squared:  0.6118, Adjusted R-squared:  0.6087 
## F-statistic: 194.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 0.608670843049297 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0564 -0.7804 -0.0120  0.9506  4.0283 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01357    0.08853 113.103   <2e-16 ***
## category_code_LT01_4_count   1.09587    0.06621  16.550   <2e-16 ***
## category_code_LT01_5_count   0.94923    0.06345  14.961   <2e-16 ***
## category_code_LT01_8_count  -0.12974    0.27886  -0.465    0.642    
## category_code_LT01_15_count  0.33577    0.76148   0.441    0.659    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 493 degrees of freedom
## Multiple R-squared:  0.6118, Adjusted R-squared:  0.6087 
## F-statistic: 194.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 0.609471624233987 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0552 -0.7774 -0.0138  0.9535  4.0282 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01370    0.08844 113.221   <2e-16 ***
## category_code_LT01_4_count   1.09623    0.06509  16.843   <2e-16 ***
## category_code_LT01_5_count   0.94725    0.06339  14.943   <2e-16 ***
## category_code_LT01_8_count  -0.14369    0.27890  -0.515    0.607    
## category_code_LT01_16_count  1.29879    1.18281   1.098    0.273    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 493 degrees of freedom
## Multiple R-squared:  0.6126, Adjusted R-squared:  0.6095 
## F-statistic: 194.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 0.614149092357132 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0025 -0.7814 -0.0050  0.9141  3.9106 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97229    0.09137 109.137   <2e-16 ***
## category_code_LT01_4_count   1.04291    0.06792  15.356   <2e-16 ***
## category_code_LT01_5_count   0.93098    0.06249  14.898   <2e-16 ***
## category_code_LT01_9_count   0.50593    0.22779   2.221   0.0268 *  
## category_code_LT01_10_count  0.14471    0.11382   1.271   0.2042    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.399 on 493 degrees of freedom
## Multiple R-squared:  0.6173, Adjusted R-squared:  0.6141 
## F-statistic: 198.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 0.625448260988864 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0269 -0.7610  0.0394  0.9405  3.7280 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00471    0.08664 115.471  < 2e-16 ***
## category_code_LT01_4_count   0.82523    0.08728   9.455  < 2e-16 ***
## category_code_LT01_5_count   0.91950    0.06164  14.917  < 2e-16 ***
## category_code_LT01_9_count   0.45022    0.22370   2.013   0.0447 *  
## category_code_LT01_11_count  0.44598    0.10967   4.067 5.55e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 493 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.6254 
## F-statistic: 208.5 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 0.613577009570886 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0289 -0.7918  0.0213  0.9447  4.0397 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00221    0.08802 113.633   <2e-16 ***
## category_code_LT01_4_count   1.04121    0.06927  15.031   <2e-16 ***
## category_code_LT01_5_count   0.92593    0.06284  14.735   <2e-16 ***
## category_code_LT01_9_count   0.53852    0.22608   2.382   0.0176 *  
## category_code_LT01_12_count  0.19424    0.20658   0.940   0.3475    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 493 degrees of freedom
## Multiple R-squared:  0.6167, Adjusted R-squared:  0.6136 
## F-statistic: 198.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 0.613284911885732 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0330 -0.7928  0.0261  0.9309  4.0386 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00329    0.08804 113.620   <2e-16 ***
## category_code_LT01_4_count   1.04824    0.06833  15.340   <2e-16 ***
## category_code_LT01_5_count   0.93032    0.06259  14.863   <2e-16 ***
## category_code_LT01_9_count   0.55289    0.22647   2.441    0.015 *  
## category_code_LT01_13_count  0.17609    0.24632   0.715    0.475    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 493 degrees of freedom
## Multiple R-squared:  0.6164, Adjusted R-squared:  0.6133 
## F-statistic:   198 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 0.612943611304104 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0345 -0.7945  0.0248  0.9123  4.0370 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00491    0.08816 113.482   <2e-16 ***
## category_code_LT01_4_count   1.05375    0.06877  15.323   <2e-16 ***
## category_code_LT01_5_count   0.93006    0.06289  14.789   <2e-16 ***
## category_code_LT01_9_count   0.53938    0.22674   2.379   0.0177 *  
## category_code_LT01_14_count  0.09145    0.33198   0.275   0.7831    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 493 degrees of freedom
## Multiple R-squared:  0.6161, Adjusted R-squared:  0.6129 
## F-statistic: 197.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 0.613060626529397 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0347 -0.7933  0.0228  0.9229  4.0381 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00374    0.08806 113.596   <2e-16 ***
## category_code_LT01_4_count   1.05191    0.06820  15.423   <2e-16 ***
## category_code_LT01_5_count   0.93209    0.06258  14.894   <2e-16 ***
## category_code_LT01_9_count   0.54530    0.22619   2.411   0.0163 *  
## category_code_LT01_15_count  0.35919    0.75723   0.474   0.6355    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 493 degrees of freedom
## Multiple R-squared:  0.6162, Adjusted R-squared:  0.6131 
## F-statistic: 197.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 0.613617230370163 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0335 -0.7935  0.0137  0.9350  4.0379 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00393    0.08800 113.681   <2e-16 ***
## category_code_LT01_4_count   1.05415    0.06703  15.726   <2e-16 ***
## category_code_LT01_5_count   0.93014    0.06255  14.869   <2e-16 ***
## category_code_LT01_9_count   0.53339    0.22625   2.358   0.0188 *  
## category_code_LT01_16_count  1.13778    1.17633   0.967   0.3339    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 493 degrees of freedom
## Multiple R-squared:  0.6167, Adjusted R-squared:  0.6136 
## F-statistic: 198.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 0.623651966892042 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0076 -0.7433  0.0365  0.9341  3.5854 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97958    0.09026 110.571  < 2e-16 ***
## category_code_LT01_4_count   0.83550    0.08729   9.572  < 2e-16 ***
## category_code_LT01_5_count   0.92792    0.06161  15.062  < 2e-16 ***
## category_code_LT01_10_count  0.14474    0.11173   1.295    0.196    
## category_code_LT01_11_count  0.45865    0.10962   4.184 3.39e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 493 degrees of freedom
## Multiple R-squared:  0.6267, Adjusted R-squared:  0.6237 
## F-statistic: 206.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 0.610949299236009 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0065 -0.7741  0.0179  0.9281  3.8802 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97240    0.09175 108.688   <2e-16 ***
## category_code_LT01_4_count   1.06216    0.06861  15.481   <2e-16 ***
## category_code_LT01_5_count   0.93664    0.06285  14.902   <2e-16 ***
## category_code_LT01_10_count  0.17230    0.11347   1.518    0.130    
## category_code_LT01_12_count  0.18990    0.20750   0.915    0.361    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 493 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.6109 
## F-statistic: 196.1 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 0.610506623871506 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0105 -0.7717  0.0239  0.9227  3.8758 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97299    0.09180 108.634   <2e-16 ***
## category_code_LT01_4_count   1.07188    0.06746  15.889   <2e-16 ***
## category_code_LT01_5_count   0.94151    0.06260  15.041   <2e-16 ***
## category_code_LT01_10_count  0.17579    0.11344   1.550    0.122    
## category_code_LT01_13_count  0.12980    0.24693   0.526    0.599    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 493 degrees of freedom
## Multiple R-squared:  0.6136, Adjusted R-squared:  0.6105 
## F-statistic: 195.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 0.610297079796145 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0115 -0.7772  0.0261  0.9193  3.8757 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97385    0.09230 108.064   <2e-16 ***
## category_code_LT01_4_count   1.07686    0.06784  15.874   <2e-16 ***
## category_code_LT01_5_count   0.94171    0.06292  14.968   <2e-16 ***
## category_code_LT01_10_count  0.17505    0.11612   1.507    0.132    
## category_code_LT01_14_count  0.03581    0.34025   0.105    0.916    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 493 degrees of freedom
## Multiple R-squared:  0.6134, Adjusted R-squared:  0.6103 
## F-statistic: 195.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 0.610362478564015 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0118 -0.7739  0.0259  0.9356  3.8764 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97348    0.09184 108.594   <2e-16 ***
## category_code_LT01_4_count   1.07480    0.06734  15.960   <2e-16 ***
## category_code_LT01_5_count   0.94267    0.06259  15.060   <2e-16 ***
## category_code_LT01_10_count  0.17475    0.11380   1.536    0.125    
## category_code_LT01_15_count  0.23355    0.76247   0.306    0.759    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 493 degrees of freedom
## Multiple R-squared:  0.6135, Adjusted R-squared:  0.6104 
## F-statistic: 195.6 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 0.611073505513763 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0109 -0.7789  0.0269  0.9394  3.8789 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97408    0.09174 108.716   <2e-16 ***
## category_code_LT01_4_count   1.07419    0.06641  16.175   <2e-16 ***
## category_code_LT01_5_count   0.94053    0.06256  15.035   <2e-16 ***
## category_code_LT01_10_count  0.17194    0.11345   1.516    0.130    
## category_code_LT01_16_count  1.17763    1.18041   0.998    0.319    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 493 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6111 
## F-statistic: 196.2 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 0.622391763123286 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0416 -0.7343  0.0290  0.9146  3.7015 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01202    0.08694 115.154  < 2e-16 ***
## category_code_LT01_4_count   0.84857    0.08691   9.764  < 2e-16 ***
## category_code_LT01_5_count   0.93015    0.06194  15.016  < 2e-16 ***
## category_code_LT01_11_count  0.47380    0.11386   4.161 3.74e-05 ***
## category_code_LT01_12_count -0.03507    0.21223  -0.165    0.869    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 493 degrees of freedom
## Multiple R-squared:  0.6254, Adjusted R-squared:  0.6224 
## F-statistic: 205.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 0.622453735805889 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0402 -0.7309  0.0327  0.9116  3.7070 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01153    0.08692 115.181  < 2e-16 ***
## category_code_LT01_4_count   0.84524    0.08734   9.677  < 2e-16 ***
## category_code_LT01_5_count   0.92876    0.06171  15.050  < 2e-16 ***
## category_code_LT01_11_count  0.46650    0.10972   4.252 2.54e-05 ***
## category_code_LT01_13_count  0.08008    0.24342   0.329    0.742    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 493 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.6225 
## F-statistic: 205.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 0.622454099410853 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0404 -0.7315  0.0331  0.9179  3.7048 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01290    0.08699 115.100  < 2e-16 ***
## category_code_LT01_4_count   0.84328    0.08816   9.565  < 2e-16 ***
## category_code_LT01_5_count   0.92717    0.06202  14.950  < 2e-16 ***
## category_code_LT01_11_count  0.46767    0.10956   4.269 2.36e-05 ***
## category_code_LT01_14_count  0.10789    0.32721   0.330    0.742    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 493 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.6225 
## F-statistic: 205.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 0.622390370181452 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0408 -0.7314  0.0318  0.9170  3.7061 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01169    0.08693 115.175  < 2e-16 ***
## category_code_LT01_4_count   0.84684    0.08731   9.699  < 2e-16 ***
## category_code_LT01_5_count   0.92941    0.06171  15.061  < 2e-16 ***
## category_code_LT01_11_count  0.46749    0.10977   4.259 2.46e-05 ***
## category_code_LT01_15_count  0.11969    0.74962   0.160    0.873    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 493 degrees of freedom
## Multiple R-squared:  0.6254, Adjusted R-squared:  0.6224 
## F-statistic: 205.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 0.623014185537501 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0395 -0.7305  0.0338  0.9170  3.7082 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01166    0.08685 115.270  < 2e-16 ***
## category_code_LT01_4_count   0.84604    0.08684   9.742  < 2e-16 ***
## category_code_LT01_5_count   0.92765    0.06167  15.041  < 2e-16 ***
## category_code_LT01_11_count  0.46452    0.10953   4.241 2.66e-05 ***
## category_code_LT01_16_count  1.06550    1.16164   0.917    0.359    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 493 degrees of freedom
## Multiple R-squared:  0.626,  Adjusted R-squared:  0.623 
## F-statistic: 206.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 0.609365031137928 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0448 -0.7954  0.0151  0.9319  4.0316 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01024    0.08843 113.197   <2e-16 ***
## category_code_LT01_4_count   1.07559    0.06856  15.689   <2e-16 ***
## category_code_LT01_5_count   0.93728    0.06299  14.879   <2e-16 ***
## category_code_LT01_12_count  0.20285    0.20774   0.976    0.329    
## category_code_LT01_13_count  0.13474    0.24727   0.545    0.586    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 493 degrees of freedom
## Multiple R-squared:  0.6125, Adjusted R-squared:  0.6094 
## F-statistic: 194.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 0.60923484313435 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0455 -0.7968 -0.0189  0.9226  4.0300 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01191    0.08853 113.094   <2e-16 ***
## category_code_LT01_4_count   1.07660    0.06923  15.550   <2e-16 ***
## category_code_LT01_5_count   0.93590    0.06327  14.791   <2e-16 ***
## category_code_LT01_12_count  0.20044    0.20828   0.962    0.336    
## category_code_LT01_14_count  0.12152    0.33373   0.364    0.716    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 493 degrees of freedom
## Multiple R-squared:  0.6124, Adjusted R-squared:  0.6092 
## F-statistic: 194.7 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 0.609289314947603 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0458 -0.7979  0.0110  0.9376  4.0314 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01044    0.08844 113.190   <2e-16 ***
## category_code_LT01_4_count   1.07643    0.06870  15.668   <2e-16 ***
## category_code_LT01_5_count   0.93843    0.06298  14.900   <2e-16 ***
## category_code_LT01_12_count  0.20739    0.20768   0.999    0.318    
## category_code_LT01_15_count  0.34142    0.76089   0.449    0.654    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 493 degrees of freedom
## Multiple R-squared:  0.6124, Adjusted R-squared:  0.6093 
## F-statistic: 194.8 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 0.610040051797881 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0442 -0.7993  0.0085  0.9383  4.0314 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01045    0.08835 113.299   <2e-16 ***
## category_code_LT01_4_count   1.07705    0.06757  15.939   <2e-16 ***
## category_code_LT01_5_count   0.93606    0.06295  14.870   <2e-16 ***
## category_code_LT01_12_count  0.20585    0.20747   0.992    0.322    
## category_code_LT01_16_count  1.26636    1.18046   1.073    0.284    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 493 degrees of freedom
## Multiple R-squared:  0.6132, Adjusted R-squared:   0.61 
## F-statistic: 195.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 0.60876233399867 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0504 -0.7751 -0.0017  0.9179  4.0283 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01361    0.08856 113.074   <2e-16 ***
## category_code_LT01_4_count   1.08582    0.06831  15.895   <2e-16 ***
## category_code_LT01_5_count   0.94056    0.06306  14.915   <2e-16 ***
## category_code_LT01_13_count  0.14202    0.24735   0.574    0.566    
## category_code_LT01_14_count  0.14613    0.33297   0.439    0.661    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 493 degrees of freedom
## Multiple R-squared:  0.6119, Adjusted R-squared:  0.6088 
## F-statistic: 194.3 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 0.608786357957881 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0510 -0.7803  0.0027  0.9250  4.0300 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01192    0.08848 113.155   <2e-16 ***
## category_code_LT01_4_count   1.08683    0.06756  16.086   <2e-16 ***
## category_code_LT01_5_count   0.94376    0.06273  15.046   <2e-16 ***
## category_code_LT01_13_count  0.14912    0.24782   0.602    0.548    
## category_code_LT01_15_count  0.36012    0.76278   0.472    0.637    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 493 degrees of freedom
## Multiple R-squared:  0.6119, Adjusted R-squared:  0.6088 
## F-statistic: 194.4 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 0.609556182758958 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0492 -0.7768  0.0034  0.9270  4.0300 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01191    0.08839 113.267   <2e-16 ***
## category_code_LT01_4_count   1.08743    0.06633  16.394   <2e-16 ***
## category_code_LT01_5_count   0.94126    0.06269  15.014   <2e-16 ***
## category_code_LT01_13_count  0.15085    0.24724   0.610    0.542    
## category_code_LT01_16_count  1.29214    1.18184   1.093    0.275    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 493 degrees of freedom
## Multiple R-squared:  0.6127, Adjusted R-squared:  0.6096 
## F-statistic:   195 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 0.60864793009894 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0516 -0.7991 -0.0003  0.9245  4.0280 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01386    0.08857 113.063   <2e-16 ***
## category_code_LT01_4_count   1.08775    0.06828  15.931   <2e-16 ***
## category_code_LT01_5_count   0.94193    0.06305  14.938   <2e-16 ***
## category_code_LT01_14_count  0.14424    0.33304   0.433    0.665    
## category_code_LT01_15_count  0.32791    0.76150   0.431    0.667    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 493 degrees of freedom
## Multiple R-squared:  0.6118, Adjusted R-squared:  0.6086 
## F-statistic: 194.2 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 0.609452081426461 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0499 -0.7974  0.0004  0.9266  4.0278 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01406    0.08848 113.181   <2e-16 ***
## category_code_LT01_4_count   1.08691    0.06728  16.154   <2e-16 ***
## category_code_LT01_5_count   0.93910    0.06302  14.901   <2e-16 ***
## category_code_LT01_14_count  0.16342    0.33306   0.491    0.624    
## category_code_LT01_16_count  1.29609    1.18271   1.096    0.274    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 493 degrees of freedom
## Multiple R-squared:  0.6126, Adjusted R-squared:  0.6095 
## F-statistic: 194.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609432744070072 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0505 -0.7821  0.0022  0.9386  4.0297 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01220    0.08840 113.254   <2e-16 ***
## category_code_LT01_4_count   1.08933    0.06633  16.423   <2e-16 ***
## category_code_LT01_5_count   0.94270    0.06268  15.040   <2e-16 ***
## category_code_LT01_15_count  0.35393    0.76096   0.465    0.642    
## category_code_LT01_16_count  1.28301    1.18180   1.086    0.278    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 493 degrees of freedom
## Multiple R-squared:  0.6126, Adjusted R-squared:  0.6094 
## F-statistic: 194.9 on 4 and 493 DF,  p-value: < 2.2e-16
## 
## ########################################
## i:  5 
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count 0.645301168218621 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9540 -0.7184  0.0543  0.8656  3.4909 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.92880    0.08514 116.623  < 2e-16 ***
## category_code_LT01_1_count  0.23463    0.08668   2.707  0.00703 ** 
## category_code_LT01_2_count  0.48510    0.08904   5.448 8.07e-08 ***
## category_code_LT01_3_count  0.20443    0.11250   1.817  0.06981 .  
## category_code_LT01_4_count  0.52636    0.10128   5.197 2.97e-07 ***
## category_code_LT01_5_count  0.92374    0.06017  15.352  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.341 on 492 degrees of freedom
## Multiple R-squared:  0.6489, Adjusted R-squared:  0.6453 
## F-statistic: 181.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count 0.630340073671924 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9715 -0.7911  0.0454  0.8471  3.4693 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.92381    0.08700 114.073  < 2e-16 ***
## category_code_LT01_1_count  0.35788    0.08422   4.250 2.56e-05 ***
## category_code_LT01_2_count  0.66006    0.08212   8.038 6.85e-15 ***
## category_code_LT01_3_count  0.34719    0.11042   3.144  0.00177 ** 
## category_code_LT01_5_count  0.95629    0.06109  15.654  < 2e-16 ***
## category_code_LT01_6_count  0.37081    0.15135   2.450  0.01463 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 492 degrees of freedom
## Multiple R-squared:  0.6341, Adjusted R-squared:  0.6303 
## F-statistic: 170.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count 0.634041502072783 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9863 -0.7397  0.0346  0.8075  3.4555 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93762    0.08648 114.910  < 2e-16 ***
## category_code_LT01_1_count  0.33922    0.08421   4.028 6.51e-05 ***
## category_code_LT01_2_count  0.65651    0.08005   8.201 2.09e-15 ***
## category_code_LT01_3_count  0.34895    0.10955   3.185 0.001538 ** 
## category_code_LT01_5_count  0.95760    0.06052  15.824  < 2e-16 ***
## category_code_LT01_7_count  0.49865    0.15008   3.323 0.000958 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.362 on 492 degrees of freedom
## Multiple R-squared:  0.6377, Adjusted R-squared:  0.634 
## F-statistic: 173.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count 0.626060395649346 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9994 -0.7551  0.0482  0.8294  3.4585 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93469    0.08744 113.612  < 2e-16 ***
## category_code_LT01_1_count  0.38248    0.08422   4.541 7.04e-06 ***
## category_code_LT01_2_count  0.72419    0.07822   9.258  < 2e-16 ***
## category_code_LT01_3_count  0.37717    0.11046   3.414 0.000692 ***
## category_code_LT01_5_count  0.98085    0.06166  15.907  < 2e-16 ***
## category_code_LT01_8_count -0.15018    0.27277  -0.551 0.582172    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6261 
## F-statistic: 167.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count 0.627259644681674 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9880 -0.7780  0.0645  0.8096  3.4620 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93119    0.08728 113.781  < 2e-16 ***
## category_code_LT01_1_count  0.37634    0.08410   4.475 9.52e-06 ***
## category_code_LT01_2_count  0.70983    0.07884   9.004  < 2e-16 ***
## category_code_LT01_3_count  0.35438    0.11136   3.182  0.00155 ** 
## category_code_LT01_5_count  0.96946    0.06099  15.894  < 2e-16 ***
## category_code_LT01_9_count  0.31074    0.22621   1.374  0.17016    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.631,  Adjusted R-squared:  0.6273 
## F-statistic: 168.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count 0.626349490383682 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9746 -0.7635  0.0271  0.8226  3.4796 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91354    0.09060 109.424  < 2e-16 ***
## category_code_LT01_1_count   0.38339    0.08419   4.554 6.65e-06 ***
## category_code_LT01_2_count   0.71851    0.07854   9.148  < 2e-16 ***
## category_code_LT01_3_count   0.35868    0.11233   3.193   0.0015 ** 
## category_code_LT01_5_count   0.97553    0.06090  16.018  < 2e-16 ***
## category_code_LT01_10_count  0.09374    0.11335   0.827   0.4086    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6263 
## F-statistic: 167.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count 0.63028562471899 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9999 -0.7766  0.0651  0.8285  3.4471 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94607    0.08707 114.229  < 2e-16 ***
## category_code_LT01_1_count   0.33457    0.08583   3.898 0.000111 ***
## category_code_LT01_2_count   0.61854    0.08916   6.938 1.26e-11 ***
## category_code_LT01_3_count   0.30815    0.11328   2.720 0.006752 ** 
## category_code_LT01_5_count   0.96511    0.06074  15.890  < 2e-16 ***
## category_code_LT01_11_count  0.28765    0.11813   2.435 0.015245 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 492 degrees of freedom
## Multiple R-squared:  0.634,  Adjusted R-squared:  0.6303 
## F-statistic: 170.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count 0.625853790760832 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9951 -0.7778  0.0480  0.8303  3.4599 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93324    0.08744 113.606  < 2e-16 ***
## category_code_LT01_1_count   0.38281    0.08487   4.511 8.09e-06 ***
## category_code_LT01_2_count   0.72695    0.07926   9.171  < 2e-16 ***
## category_code_LT01_3_count   0.37680    0.11060   3.407 0.000711 ***
## category_code_LT01_5_count   0.97674    0.06127  15.942  < 2e-16 ***
## category_code_LT01_12_count -0.03661    0.20699  -0.177 0.859676    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 492 degrees of freedom
## Multiple R-squared:  0.6296, Adjusted R-squared:  0.6259 
## F-statistic: 167.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count 0.625841213245675 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9944 -0.7730  0.0482  0.8312  3.4597 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93347    0.08744 113.602  < 2e-16 ***
## category_code_LT01_1_count   0.37930    0.08526   4.449 1.07e-05 ***
## category_code_LT01_2_count   0.72407    0.07841   9.234  < 2e-16 ***
## category_code_LT01_3_count   0.37576    0.11047   3.401 0.000725 ***
## category_code_LT01_5_count   0.97531    0.06100  15.989  < 2e-16 ***
## category_code_LT01_13_count  0.02966    0.24423   0.121 0.903397    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 492 degrees of freedom
## Multiple R-squared:  0.6296, Adjusted R-squared:  0.6258 
## F-statistic: 167.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count 0.626029752359783 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9940 -0.7701  0.0464  0.8287  3.4574 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93571    0.08753 113.506  < 2e-16 ***
## category_code_LT01_1_count   0.37459    0.08508   4.403 1.31e-05 ***
## category_code_LT01_2_count   0.71942    0.07889   9.119  < 2e-16 ***
## category_code_LT01_3_count   0.37781    0.11051   3.419 0.000681 ***
## category_code_LT01_5_count   0.97149    0.06146  15.807  < 2e-16 ***
## category_code_LT01_14_count  0.16725    0.32626   0.513 0.608434    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.626 
## F-statistic: 167.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_15_count 0.62622374799973 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9923 -0.7800  0.0711  0.8306  3.4614 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93171    0.08742 113.609  < 2e-16 ***
## category_code_LT01_1_count   0.39100    0.08531   4.583 5.81e-06 ***
## category_code_LT01_2_count   0.72585    0.07822   9.280  < 2e-16 ***
## category_code_LT01_3_count   0.38399    0.11099   3.460 0.000588 ***
## category_code_LT01_5_count   0.97489    0.06092  16.002  < 2e-16 ***
## category_code_LT01_15_count -0.54780    0.76091  -0.720 0.471914    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6262 
## F-statistic: 167.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_16_count 0.625830092682591 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9945 -0.7744  0.0483  0.8309  3.4598 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93333    0.08744 113.597  < 2e-16 ***
## category_code_LT01_1_count   0.38087    0.08435   4.516 7.91e-06 ***
## category_code_LT01_2_count   0.72477    0.07850   9.233  < 2e-16 ***
## category_code_LT01_3_count   0.37596    0.11096   3.388  0.00076 ***
## category_code_LT01_5_count   0.97563    0.06095  16.008  < 2e-16 ***
## category_code_LT01_16_count -0.01299    1.16993  -0.011  0.99114    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 492 degrees of freedom
## Multiple R-squared:  0.6296, Adjusted R-squared:  0.6258 
## F-statistic: 167.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 0.645443215095747 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9495 -0.7639  0.0832  0.8551  3.4966 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.92647    0.08516 116.557  < 2e-16 ***
## category_code_LT01_1_count  0.24229    0.08626   2.809  0.00517 ** 
## category_code_LT01_2_count  0.48265    0.08919   5.411 9.79e-08 ***
## category_code_LT01_4_count  0.54923    0.09823   5.592 3.74e-08 ***
## category_code_LT01_5_count  0.92068    0.06031  15.267  < 2e-16 ***
## category_code_LT01_6_count  0.27978    0.14954   1.871  0.06195 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.341 on 492 degrees of freedom
## Multiple R-squared:  0.649,  Adjusted R-squared:  0.6454 
## F-statistic:   182 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 0.647180319459494 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9629 -0.7268  0.0517  0.8255  3.4816 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93720    0.08488 117.075  < 2e-16 ***
## category_code_LT01_1_count  0.23576    0.08615   2.737  0.00643 ** 
## category_code_LT01_2_count  0.49258    0.08737   5.638 2.91e-08 ***
## category_code_LT01_4_count  0.53027    0.09873   5.371 1.21e-07 ***
## category_code_LT01_5_count  0.92453    0.05990  15.436  < 2e-16 ***
## category_code_LT01_7_count  0.36616    0.15024   2.437  0.01516 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.338 on 492 degrees of freedom
## Multiple R-squared:  0.6507, Adjusted R-squared:  0.6472 
## F-statistic: 183.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 0.643139485364286 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9703 -0.7502  0.0775  0.8481  3.4687 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93506    0.08539 116.355  < 2e-16 ***
## category_code_LT01_1_count  0.25466    0.08639   2.948  0.00335 ** 
## category_code_LT01_2_count  0.52061    0.08709   5.978 4.35e-09 ***
## category_code_LT01_4_count  0.58087    0.09713   5.980 4.29e-09 ***
## category_code_LT01_5_count  0.93823    0.06085  15.418  < 2e-16 ***
## category_code_LT01_8_count -0.14631    0.26642  -0.549  0.58315    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.345 on 492 degrees of freedom
## Multiple R-squared:  0.6467, Adjusted R-squared:  0.6431 
## F-statistic: 180.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 0.644547286058996 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9577 -0.7221  0.0925  0.8756  3.4863 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93096    0.08520 116.557  < 2e-16 ***
## category_code_LT01_1_count  0.24733    0.08626   2.867  0.00432 ** 
## category_code_LT01_2_count  0.50316    0.08772   5.736 1.70e-08 ***
## category_code_LT01_4_count  0.57094    0.09714   5.878 7.68e-09 ***
## category_code_LT01_5_count  0.92596    0.06020  15.380  < 2e-16 ***
## category_code_LT01_9_count  0.32885    0.21917   1.500  0.13414    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 492 degrees of freedom
## Multiple R-squared:  0.6481, Adjusted R-squared:  0.6445 
## F-statistic: 181.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 0.64368172759474 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9408 -0.7481  0.1049  0.8741  3.3778 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90964    0.08846 112.021  < 2e-16 ***
## category_code_LT01_1_count   0.25492    0.08629   2.954  0.00329 ** 
## category_code_LT01_2_count   0.51124    0.08754   5.840 9.49e-09 ***
## category_code_LT01_4_count   0.57274    0.09733   5.884 7.40e-09 ***
## category_code_LT01_5_count   0.93232    0.06009  15.515  < 2e-16 ***
## category_code_LT01_10_count  0.11183    0.10910   1.025  0.30584    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.344 on 492 degrees of freedom
## Multiple R-squared:  0.6473, Adjusted R-squared:  0.6437 
## F-statistic: 180.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 0.644823850538977 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9701 -0.7387  0.0544  0.8463  3.4728 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94169    0.08529 116.562  < 2e-16 ***
## category_code_LT01_1_count   0.23019    0.08729   2.637  0.00862 ** 
## category_code_LT01_2_count   0.46260    0.09403   4.920 1.18e-06 ***
## category_code_LT01_4_count   0.53347    0.10110   5.277 1.98e-07 ***
## category_code_LT01_5_count   0.92845    0.06006  15.459  < 2e-16 ***
## category_code_LT01_11_count  0.19015    0.11711   1.624  0.10509    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 492 degrees of freedom
## Multiple R-squared:  0.6484, Adjusted R-squared:  0.6448 
## F-statistic: 181.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 0.642963768395988 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9663 -0.7609  0.0779  0.8462  3.4742 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93360    0.08537 116.354  < 2e-16 ***
## category_code_LT01_1_count   0.25556    0.08695   2.939  0.00345 ** 
## category_code_LT01_2_count   0.52392    0.08793   5.958 4.86e-09 ***
## category_code_LT01_4_count   0.58124    0.09722   5.978 4.33e-09 ***
## category_code_LT01_5_count   0.93459    0.06046  15.459  < 2e-16 ***
## category_code_LT01_12_count -0.04921    0.20211  -0.243  0.80774    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 492 degrees of freedom
## Multiple R-squared:  0.6466, Adjusted R-squared:  0.643 
## F-statistic:   180 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 0.642929069450835 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9654 -0.7698  0.0794  0.8547  3.4756 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93361    0.08538 116.342  < 2e-16 ***
## category_code_LT01_1_count   0.25437    0.08717   2.918  0.00368 ** 
## category_code_LT01_2_count   0.52131    0.08716   5.981 4.27e-09 ***
## category_code_LT01_4_count   0.58075    0.09724   5.972 4.49e-09 ***
## category_code_LT01_5_count   0.93332    0.06019  15.507  < 2e-16 ***
## category_code_LT01_13_count -0.02557    0.23880  -0.107  0.91477    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 492 degrees of freedom
## Multiple R-squared:  0.6465, Adjusted R-squared:  0.6429 
## F-statistic:   180 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 0.642939564081262 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9653 -0.7524  0.0790  0.8621  3.4753 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93295    0.08551 116.161  < 2e-16 ***
## category_code_LT01_1_count   0.25445    0.08677   2.932  0.00352 ** 
## category_code_LT01_2_count   0.52159    0.08719   5.982 4.24e-09 ***
## category_code_LT01_4_count   0.58180    0.09759   5.962 4.77e-09 ***
## category_code_LT01_5_count   0.93415    0.06050  15.441  < 2e-16 ***
## category_code_LT01_14_count -0.05153    0.32003  -0.161  0.87215    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 492 degrees of freedom
## Multiple R-squared:  0.6465, Adjusted R-squared:  0.6429 
## F-statistic:   180 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 0.643084909817089 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9644 -0.7504  0.0793  0.8455  3.4768 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93281    0.08538 116.337  < 2e-16 ***
## category_code_LT01_1_count   0.26026    0.08765   2.969  0.00313 ** 
## category_code_LT01_2_count   0.52300    0.08720   5.998 3.87e-09 ***
## category_code_LT01_4_count   0.58107    0.09715   5.981 4.26e-09 ***
## category_code_LT01_5_count   0.93295    0.06014  15.513  < 2e-16 ***
## category_code_LT01_15_count -0.35191    0.73977  -0.476  0.63450    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 492 degrees of freedom
## Multiple R-squared:  0.6467, Adjusted R-squared:  0.6431 
## F-statistic: 180.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 0.643066199955331 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9653 -0.7589  0.0803  0.8637  3.4760 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93405    0.08536 116.374  < 2e-16 ***
## category_code_LT01_1_count   0.25413    0.08638   2.942  0.00342 ** 
## category_code_LT01_2_count   0.51622    0.08775   5.883 7.44e-09 ***
## category_code_LT01_4_count   0.58127    0.09716   5.983 4.23e-09 ***
## category_code_LT01_5_count   0.93252    0.06015  15.502  < 2e-16 ***
## category_code_LT01_16_count  0.50950    1.13789   0.448  0.65452    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 492 degrees of freedom
## Multiple R-squared:  0.6467, Adjusted R-squared:  0.6431 
## F-statistic: 180.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 0.632150161920961 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9865 -0.7742  0.0390  0.9143  3.4568 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93637    0.08675 114.545  < 2e-16 ***
## category_code_LT01_1_count  0.36765    0.08310   4.424 1.19e-05 ***
## category_code_LT01_2_count  0.68266    0.07856   8.690  < 2e-16 ***
## category_code_LT01_5_count  0.95982    0.06074  15.803  < 2e-16 ***
## category_code_LT01_6_count  0.41294    0.15015   2.750  0.00617 ** 
## category_code_LT01_7_count  0.52751    0.15007   3.515  0.00048 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.366 on 492 degrees of freedom
## Multiple R-squared:  0.6359, Adjusted R-squared:  0.6322 
## F-statistic: 171.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 0.623176387020662 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0022 -0.8020  0.0319  0.9492  3.4593 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93381    0.08782 113.113  < 2e-16 ***
## category_code_LT01_1_count  0.41787    0.08299   5.035  6.7e-07 ***
## category_code_LT01_2_count  0.76155    0.07614  10.002  < 2e-16 ***
## category_code_LT01_5_count  0.98614    0.06189  15.933  < 2e-16 ***
## category_code_LT01_6_count  0.42482    0.15207   2.794  0.00542 ** 
## category_code_LT01_8_count -0.16087    0.27398  -0.587  0.55738    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 492 degrees of freedom
## Multiple R-squared:  0.627,  Adjusted R-squared:  0.6232 
## F-statistic: 165.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 0.625113574654028 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9878 -0.7962  0.0813  0.9429  3.4638 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.92937    0.08758 113.371  < 2e-16 ***
## category_code_LT01_1_count  0.40682    0.08291   4.907 1.26e-06 ***
## category_code_LT01_2_count  0.73803    0.07727   9.551  < 2e-16 ***
## category_code_LT01_5_count  0.97171    0.06125  15.865  < 2e-16 ***
## category_code_LT01_6_count  0.40862    0.15174   2.693  0.00732 ** 
## category_code_LT01_9_count  0.38222    0.22488   1.700  0.08982 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6289, Adjusted R-squared:  0.6251 
## F-statistic: 166.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 0.623680587574491 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9729 -0.8077  0.0213  0.9594  3.4846 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90854    0.09091 108.990  < 2e-16 ***
## category_code_LT01_1_count   0.41738    0.08289   5.035 6.71e-07 ***
## category_code_LT01_2_count   0.75310    0.07663   9.827  < 2e-16 ***
## category_code_LT01_5_count   0.98034    0.06114  16.034  < 2e-16 ***
## category_code_LT01_6_count   0.39633    0.15386   2.576   0.0103 *  
## category_code_LT01_10_count  0.11352    0.11328   1.002   0.3167    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 492 degrees of freedom
## Multiple R-squared:  0.6275, Adjusted R-squared:  0.6237 
## F-statistic: 165.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 0.628932657223291 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0010 -0.7950  0.0579  0.8726  3.4468 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94640    0.08726 113.989  < 2e-16 ***
## category_code_LT01_1_count   0.35432    0.08517   4.160 3.76e-05 ***
## category_code_LT01_2_count   0.62880    0.08912   7.056 5.86e-12 ***
## category_code_LT01_5_count   0.96618    0.06093  15.858  < 2e-16 ***
## category_code_LT01_6_count   0.35983    0.15234   2.362  0.01856 *  
## category_code_LT01_11_count  0.32748    0.11591   2.825  0.00492 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.372 on 492 degrees of freedom
## Multiple R-squared:  0.6327, Adjusted R-squared:  0.6289 
## F-statistic: 169.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 0.622971905856743 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9979 -0.8118  0.0348  0.9522  3.4610 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93219    0.08782 113.099  < 2e-16 ***
## category_code_LT01_1_count   0.41919    0.08364   5.012 7.52e-07 ***
## category_code_LT01_2_count   0.76560    0.07703   9.939  < 2e-16 ***
## category_code_LT01_5_count   0.98229    0.06148  15.977  < 2e-16 ***
## category_code_LT01_6_count   0.42532    0.15271   2.785  0.00556 ** 
## category_code_LT01_12_count -0.05813    0.20851  -0.279  0.78053    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 492 degrees of freedom
## Multiple R-squared:  0.6268, Adjusted R-squared:  0.623 
## F-statistic: 165.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 0.622944437370441 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9968 -0.8075  0.0430  0.9366  3.4605 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93261    0.08782 113.099  < 2e-16 ***
## category_code_LT01_1_count   0.41340    0.08411   4.915 1.21e-06 ***
## category_code_LT01_2_count   0.76111    0.07640   9.963  < 2e-16 ***
## category_code_LT01_5_count   0.98006    0.06126  15.998  < 2e-16 ***
## category_code_LT01_6_count   0.42192    0.15204   2.775  0.00573 ** 
## category_code_LT01_13_count  0.05018    0.24524   0.205  0.83795    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 492 degrees of freedom
## Multiple R-squared:  0.6267, Adjusted R-squared:  0.6229 
## F-statistic: 165.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 0.623235422614448 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9960 -0.8124  0.0464  0.9570  3.4579 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93527    0.08789 113.039  < 2e-16 ***
## category_code_LT01_1_count   0.40790    0.08392   4.861 1.58e-06 ***
## category_code_LT01_2_count   0.75463    0.07705   9.794  < 2e-16 ***
## category_code_LT01_5_count   0.97503    0.06178  15.782  < 2e-16 ***
## category_code_LT01_6_count   0.43029    0.15258   2.820  0.00499 ** 
## category_code_LT01_14_count  0.21348    0.32867   0.650  0.51630    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 492 degrees of freedom
## Multiple R-squared:  0.627,  Adjusted R-squared:  0.6232 
## F-statistic: 165.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 0.623071054085462 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9960 -0.8085  0.0435  0.9468  3.4617 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93149    0.08783 113.080  < 2e-16 ***
## category_code_LT01_1_count   0.42336    0.08441   5.015 7.41e-07 ***
## category_code_LT01_2_count   0.76432    0.07626  10.023  < 2e-16 ***
## category_code_LT01_5_count   0.98046    0.06119  16.023  < 2e-16 ***
## category_code_LT01_6_count   0.42339    0.15205   2.785  0.00557 ** 
## category_code_LT01_15_count -0.34614    0.76051  -0.455  0.64921    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 492 degrees of freedom
## Multiple R-squared:  0.6269, Adjusted R-squared:  0.6231 
## F-statistic: 165.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 0.623160257565 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9965 -0.8025  0.0460  0.9492  3.4605 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93265    0.08779 113.137  < 2e-16 ***
## category_code_LT01_1_count   0.41739    0.08297   5.031 6.86e-07 ***
## category_code_LT01_2_count   0.75519    0.07716   9.787  < 2e-16 ***
## category_code_LT01_5_count   0.97956    0.06121  16.003  < 2e-16 ***
## category_code_LT01_6_count   0.42930    0.15262   2.813  0.00511 ** 
## category_code_LT01_16_count  0.66792    1.17403   0.569  0.56967    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 492 degrees of freedom
## Multiple R-squared:  0.627,  Adjusted R-squared:  0.6232 
## F-statistic: 165.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 0.626758942541385 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0200 -0.7727  0.0264  0.9165  3.4437 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94945    0.08731  113.95  < 2e-16 ***
## category_code_LT01_1_count  0.40007    0.08299    4.82 1.91e-06 ***
## category_code_LT01_2_count  0.76344    0.07332   10.41  < 2e-16 ***
## category_code_LT01_5_count  0.98918    0.06129   16.14  < 2e-16 ***
## category_code_LT01_7_count  0.53683    0.15123    3.55 0.000422 ***
## category_code_LT01_8_count -0.16081    0.27259   -0.59 0.555504    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 492 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.6268 
## F-statistic: 167.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 0.628182907689188 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0062 -0.7902  0.0645  0.9157  3.4484 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94479    0.08714 114.130  < 2e-16 ***
## category_code_LT01_1_count  0.39142    0.08292   4.720 3.07e-06 ***
## category_code_LT01_2_count  0.74387    0.07440   9.998  < 2e-16 ***
## category_code_LT01_5_count  0.97601    0.06065  16.092  < 2e-16 ***
## category_code_LT01_7_count  0.51133    0.15162   3.372 0.000804 ***
## category_code_LT01_9_count  0.33599    0.22482   1.495 0.135681    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 492 degrees of freedom
## Multiple R-squared:  0.6319, Adjusted R-squared:  0.6282 
## F-statistic: 168.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 0.627465974592533 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9862 -0.7734  0.0593  0.9201  3.4727 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92045    0.09051 109.605  < 2e-16 ***
## category_code_LT01_1_count   0.39903    0.08287   4.815 1.96e-06 ***
## category_code_LT01_2_count   0.75050    0.07420  10.114  < 2e-16 ***
## category_code_LT01_5_count   0.98226    0.06051  16.233  < 2e-16 ***
## category_code_LT01_7_count   0.51863    0.15161   3.421 0.000676 ***
## category_code_LT01_10_count  0.12647    0.11168   1.132 0.257995    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6312, Adjusted R-squared:  0.6275 
## F-statistic: 168.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 0.630690636306077 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0164 -0.7473  0.0343  0.8590  3.4354 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95777    0.08691 114.569  < 2e-16 ***
## category_code_LT01_1_count   0.35035    0.08498   4.123 4.39e-05 ***
## category_code_LT01_2_count   0.65393    0.08651   7.559 2.01e-13 ***
## category_code_LT01_5_count   0.97201    0.06044  16.083  < 2e-16 ***
## category_code_LT01_7_count   0.43880    0.15565   2.819  0.00501 ** 
## category_code_LT01_11_count  0.28012    0.11848   2.364  0.01845 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 492 degrees of freedom
## Multiple R-squared:  0.6344, Adjusted R-squared:  0.6307 
## F-statistic: 170.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 0.626494952487153 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.7806  0.0413  0.9192  3.4452 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.947950   0.087308 113.940  < 2e-16 ***
## category_code_LT01_1_count  0.398352   0.083794   4.754 2.62e-06 ***
## category_code_LT01_2_count  0.763882   0.074769  10.217  < 2e-16 ***
## category_code_LT01_5_count  0.983552   0.060953  16.136  < 2e-16 ***
## category_code_LT01_7_count  0.533971   0.151203   3.531 0.000452 ***
## category_code_LT01_12_count 0.001271   0.206560   0.006 0.995092    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 492 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6265 
## F-statistic: 167.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 0.626542303277147 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0147 -0.7845  0.0377  0.9110  3.4454 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94773    0.08731 113.941  < 2e-16 ***
## category_code_LT01_1_count   0.40143    0.08384   4.788 2.23e-06 ***
## category_code_LT01_2_count   0.76468    0.07339  10.419  < 2e-16 ***
## category_code_LT01_5_count   0.98408    0.06061  16.237  < 2e-16 ***
## category_code_LT01_7_count   0.53816    0.15212   3.538 0.000442 ***
## category_code_LT01_13_count -0.06133    0.24550  -0.250 0.802817    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 492 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6265 
## F-statistic: 167.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 0.626508262671907 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0145 -0.7755  0.0449  0.8993  3.4446 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94856    0.08743 113.790  < 2e-16 ***
## category_code_LT01_1_count   0.39701    0.08366   4.746 2.73e-06 ***
## category_code_LT01_2_count   0.76300    0.07370  10.352  < 2e-16 ***
## category_code_LT01_5_count   0.98262    0.06102  16.104  < 2e-16 ***
## category_code_LT01_7_count   0.53248    0.15162   3.512 0.000486 ***
## category_code_LT01_14_count  0.04331    0.32676   0.133 0.894598    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 492 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6265 
## F-statistic: 167.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 0.626528059217274 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0142 -0.7678  0.0388  0.9100  3.4456 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94753    0.08733 113.913  < 2e-16 ***
## category_code_LT01_1_count   0.40189    0.08462   4.750 2.68e-06 ***
## category_code_LT01_2_count   0.76529    0.07361  10.397  < 2e-16 ***
## category_code_LT01_5_count   0.98362    0.06058  16.238  < 2e-16 ***
## category_code_LT01_7_count   0.53253    0.15135   3.519 0.000474 ***
## category_code_LT01_15_count -0.15825    0.75742  -0.209 0.834590    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 492 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6265 
## F-statistic: 167.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 0.626596031615205 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.7750  0.0435  0.9231  3.4449 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94824    0.08730 113.956  < 2e-16 ***
## category_code_LT01_1_count   0.39947    0.08301   4.812 1.99e-06 ***
## category_code_LT01_2_count   0.76031    0.07401  10.272  < 2e-16 ***
## category_code_LT01_5_count   0.98317    0.06058  16.229  < 2e-16 ***
## category_code_LT01_7_count   0.53484    0.15120   3.537 0.000443 ***
## category_code_LT01_16_count  0.42475    1.16371   0.365 0.715273    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 492 degrees of freedom
## Multiple R-squared:  0.6304, Adjusted R-squared:  0.6266 
## F-statistic: 167.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 0.619808407738866 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0198 -0.7905  0.0124  0.9013  3.4513 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94184    0.08814 112.801  < 2e-16 ***
## category_code_LT01_1_count  0.43871    0.08278   5.300 1.76e-07 ***
## category_code_LT01_2_count  0.81703    0.07193  11.358  < 2e-16 ***
## category_code_LT01_5_count  0.99986    0.06182  16.174  < 2e-16 ***
## category_code_LT01_8_count -0.14703    0.27514  -0.534   0.5933    
## category_code_LT01_9_count  0.41587    0.22633   1.837   0.0667 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6236, Adjusted R-squared:  0.6198 
## F-statistic:   163 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 0.618805066153215 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9937 -0.7936  0.0107  0.9039  3.4828 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91040    0.09152 108.288  < 2e-16 ***
## category_code_LT01_1_count   0.44884    0.08267   5.429 8.91e-08 ***
## category_code_LT01_2_count   0.82595    0.07165  11.528  < 2e-16 ***
## category_code_LT01_5_count   1.00762    0.06168  16.335  < 2e-16 ***
## category_code_LT01_8_count  -0.13979    0.27543  -0.508    0.612    
## category_code_LT01_10_count  0.16203    0.11255   1.440    0.151    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 492 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.6188 
## F-statistic: 162.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 0.624851638000497 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0293 -0.7485  0.0394  0.8969  3.4342 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95891    0.08763 113.644  < 2e-16 ***
## category_code_LT01_1_count   0.37525    0.08532   4.398 1.34e-05 ***
## category_code_LT01_2_count   0.68352    0.08657   7.895 1.90e-14 ***
## category_code_LT01_5_count   0.98899    0.06153  16.074  < 2e-16 ***
## category_code_LT01_8_count  -0.11147    0.27321  -0.408  0.68345    
## category_code_LT01_11_count  0.36552    0.11538   3.168  0.00163 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6249 
## F-statistic: 166.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 0.617199399466322 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0302 -0.7930 -0.0006  0.9042  3.4478 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.945395   0.088419 112.481  < 2e-16 ***
## category_code_LT01_1_count   0.449702   0.083660   5.375 1.18e-07 ***
## category_code_LT01_2_count   0.846135   0.071901  11.768  < 2e-16 ***
## category_code_LT01_5_count   1.009715   0.062132  16.251  < 2e-16 ***
## category_code_LT01_8_count  -0.129864   0.276087  -0.470    0.638    
## category_code_LT01_12_count  0.001507   0.209240   0.007    0.994    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6172 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 0.617208886927589 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0300 -0.7930  0.0002  0.9047  3.4477 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94548    0.08842 112.480  < 2e-16 ***
## category_code_LT01_1_count   0.44825    0.08400   5.336 1.45e-07 ***
## category_code_LT01_2_count   0.84564    0.07061  11.977  < 2e-16 ***
## category_code_LT01_5_count   1.00940    0.06188  16.312  < 2e-16 ***
## category_code_LT01_8_count  -0.12790    0.27645  -0.463    0.644    
## category_code_LT01_13_count  0.02739    0.24751   0.111    0.912    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6172 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 0.617320995121488 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0300 -0.7945  0.0019  0.8889  3.4459 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94729    0.08853 112.356  < 2e-16 ***
## category_code_LT01_1_count   0.44513    0.08366   5.321 1.57e-07 ***
## category_code_LT01_2_count   0.84262    0.07098  11.872  < 2e-16 ***
## category_code_LT01_5_count   1.00671    0.06227  16.168  < 2e-16 ***
## category_code_LT01_8_count  -0.13119    0.27590  -0.476    0.635    
## category_code_LT01_14_count  0.13045    0.32987   0.395    0.693    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6173 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 0.617301022510657 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0294 -0.7964  0.0102  0.8993  3.4485 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94468    0.08843 112.462  < 2e-16 ***
## category_code_LT01_1_count   0.45561    0.08439   5.399 1.04e-07 ***
## category_code_LT01_2_count   0.84815    0.07058  12.016  < 2e-16 ***
## category_code_LT01_5_count   1.00969    0.06179  16.341  < 2e-16 ***
## category_code_LT01_8_count  -0.12916    0.27589  -0.468    0.640    
## category_code_LT01_15_count -0.27691    0.76594  -0.362    0.718    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6173 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 0.617284120799213 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0304 -0.7932 -0.0022  0.9058  3.4475 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94570    0.08841 112.493  < 2e-16 ***
## category_code_LT01_1_count   0.45087    0.08290   5.439 8.47e-08 ***
## category_code_LT01_2_count   0.84300    0.07107  11.862  < 2e-16 ***
## category_code_LT01_5_count   1.00957    0.06179  16.338  < 2e-16 ***
## category_code_LT01_8_count  -0.13451    0.27626  -0.487    0.627    
## category_code_LT01_16_count  0.38937    1.17956   0.330    0.741    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6173 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 0.620729091552431 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9845 -0.7879  0.0377  0.9227  3.4821 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91103    0.09127 108.587  < 2e-16 ***
## category_code_LT01_1_count   0.43709    0.08263   5.290 1.84e-07 ***
## category_code_LT01_2_count   0.80256    0.07287  11.013  < 2e-16 ***
## category_code_LT01_5_count   0.99348    0.06101  16.284  < 2e-16 ***
## category_code_LT01_9_count   0.37782    0.22764   1.660   0.0976 .  
## category_code_LT01_10_count  0.13760    0.11308   1.217   0.2243    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 492 degrees of freedom
## Multiple R-squared:  0.6245, Adjusted R-squared:  0.6207 
## F-statistic: 163.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 0.626774081129305 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0158 -0.7896  0.0652  0.8493  3.4390 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95419    0.08740 113.887  < 2e-16 ***
## category_code_LT01_1_count   0.36609    0.08515   4.300 2.06e-05 ***
## category_code_LT01_2_count   0.66243    0.08726   7.592 1.60e-13 ***
## category_code_LT01_5_count   0.97629    0.06081  16.055  < 2e-16 ***
## category_code_LT01_9_count   0.36907    0.22454   1.644   0.1009    
## category_code_LT01_11_count  0.35481    0.11528   3.078   0.0022 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 492 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.6268 
## F-statistic: 167.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 0.619587828152449 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0150 -0.8033  0.0278  0.9099  3.4526 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94052    0.08813 112.796  < 2e-16 ***
## category_code_LT01_1_count   0.43720    0.08357   5.231  2.5e-07 ***
## category_code_LT01_2_count   0.81756    0.07341  11.137  < 2e-16 ***
## category_code_LT01_5_count   0.99482    0.06147  16.185  < 2e-16 ***
## category_code_LT01_9_count   0.41175    0.22626   1.820   0.0694 .  
## category_code_LT01_12_count -0.00222    0.20846  -0.011   0.9915    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6234, Adjusted R-squared:  0.6196 
## F-statistic: 162.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 0.619642048059107 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.8088  0.0214  0.9077  3.4524 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94075    0.08813 112.802  < 2e-16 ***
## category_code_LT01_1_count   0.43334    0.08393   5.163 3.53e-07 ***
## category_code_LT01_2_count   0.81567    0.07224  11.291  < 2e-16 ***
## category_code_LT01_5_count   0.99395    0.06116  16.251  < 2e-16 ***
## category_code_LT01_9_count   0.41586    0.22678   1.834   0.0673 .  
## category_code_LT01_13_count  0.06542    0.24682   0.265   0.7911    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6196 
## F-statistic: 162.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 0.619646152576912 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0148 -0.8094  0.0221  0.9101  3.4513 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94187    0.08826 112.647   <2e-16 ***
## category_code_LT01_1_count   0.43394    0.08352   5.195    3e-07 ***
## category_code_LT01_2_count   0.81517    0.07240  11.259   <2e-16 ***
## category_code_LT01_5_count   0.99270    0.06154  16.130   <2e-16 ***
## category_code_LT01_9_count   0.40777    0.22671   1.799   0.0727 .  
## category_code_LT01_14_count  0.09057    0.32951   0.275   0.7835    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6196 
## F-statistic: 162.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 0.619661079051025 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0143 -0.8071  0.0315  0.9066  3.4532 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93994    0.08814 112.775  < 2e-16 ***
## category_code_LT01_1_count   0.44209    0.08433   5.242 2.36e-07 ***
## category_code_LT01_2_count   0.81918    0.07218  11.350  < 2e-16 ***
## category_code_LT01_5_count   0.99477    0.06109  16.284  < 2e-16 ***
## category_code_LT01_9_count   0.40954    0.22636   1.809    0.071 .  
## category_code_LT01_15_count -0.23530    0.76394  -0.308    0.758    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6197 
## F-statistic: 162.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 0.619636394384891 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0150 -0.8033  0.0279  0.9169  3.4524 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94074    0.08813 112.801  < 2e-16 ***
## category_code_LT01_1_count   0.43790    0.08281   5.288 1.86e-07 ***
## category_code_LT01_2_count   0.81507    0.07254  11.236  < 2e-16 ***
## category_code_LT01_5_count   0.99452    0.06110  16.278  < 2e-16 ***
## category_code_LT01_9_count   0.41002    0.22635   1.811   0.0707 .  
## category_code_LT01_16_count  0.29474    1.17490   0.251   0.8020    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6196 
## F-statistic: 162.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 0.625947557685838 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9934 -0.7766  0.0401  0.8890  3.4662 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92696    0.09081 109.312  < 2e-16 ***
## category_code_LT01_1_count   0.37443    0.08512   4.399 1.33e-05 ***
## category_code_LT01_2_count   0.66899    0.08716   7.676 8.93e-14 ***
## category_code_LT01_5_count   0.98324    0.06066  16.208  < 2e-16 ***
## category_code_LT01_10_count  0.14157    0.11162   1.268    0.205    
## category_code_LT01_11_count  0.35849    0.11536   3.108    0.002 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6297, Adjusted R-squared:  0.6259 
## F-statistic: 167.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 0.618609181186503 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9895 -0.7931  0.0247  0.9006  3.4838 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90932    0.09153 108.258  < 2e-16 ***
## category_code_LT01_1_count   0.44800    0.08346   5.368 1.23e-07 ***
## category_code_LT01_2_count   0.82718    0.07302  11.328  < 2e-16 ***
## category_code_LT01_5_count   1.00314    0.06130  16.365  < 2e-16 ***
## category_code_LT01_10_count  0.16091    0.11264   1.429    0.154    
## category_code_LT01_12_count -0.01443    0.20891  -0.069    0.945    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 492 degrees of freedom
## Multiple R-squared:  0.6224, Adjusted R-squared:  0.6186 
## F-statistic: 162.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 0.618612225911031 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9893 -0.7914  0.0226  0.8961  3.4836 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90959    0.09154 108.255  < 2e-16 ***
## category_code_LT01_1_count   0.44592    0.08375   5.325 1.54e-07 ***
## category_code_LT01_2_count   0.82574    0.07184  11.495  < 2e-16 ***
## category_code_LT01_5_count   1.00244    0.06098  16.438  < 2e-16 ***
## category_code_LT01_10_count  0.16024    0.11260   1.423    0.155    
## category_code_LT01_13_count  0.02301    0.24671   0.093    0.926    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 492 degrees of freedom
## Multiple R-squared:  0.6224, Adjusted R-squared:  0.6186 
## F-statistic: 162.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 0.61861037127074 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9897 -0.7951  0.0227  0.8984  3.4829 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91025    0.09211 107.596  < 2e-16 ***
## category_code_LT01_1_count   0.44624    0.08349   5.345 1.38e-07 ***
## category_code_LT01_2_count   0.82572    0.07193  11.479  < 2e-16 ***
## category_code_LT01_5_count   1.00207    0.06140  16.319  < 2e-16 ***
## category_code_LT01_10_count  0.15858    0.11534   1.375    0.170    
## category_code_LT01_14_count  0.02680    0.33748   0.079    0.937    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 492 degrees of freedom
## Multiple R-squared:  0.6224, Adjusted R-squared:  0.6186 
## F-statistic: 162.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 0.618788123562164 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9873 -0.7893  0.0359  0.8936  3.4857 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90749    0.09159 108.175  < 2e-16 ***
## category_code_LT01_1_count   0.45500    0.08416   5.406 1.01e-07 ***
## category_code_LT01_2_count   0.82821    0.07177  11.540  < 2e-16 ***
## category_code_LT01_5_count   1.00255    0.06091  16.458  < 2e-16 ***
## category_code_LT01_10_count  0.16514    0.11291   1.463    0.144    
## category_code_LT01_15_count -0.37243    0.76709  -0.486    0.628    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 492 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.6188 
## F-statistic: 162.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 0.618655718572225 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9896 -0.7917  0.0239  0.8969  3.4833 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90985    0.09153 108.267  < 2e-16 ***
## category_code_LT01_1_count   0.44799    0.08269   5.418 9.45e-08 ***
## category_code_LT01_2_count   0.82385    0.07226  11.402  < 2e-16 ***
## category_code_LT01_5_count   1.00242    0.06093  16.451  < 2e-16 ***
## category_code_LT01_10_count  0.15955    0.11261   1.417    0.157    
## category_code_LT01_16_count  0.29955    1.17663   0.255    0.799    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 492 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6187 
## F-statistic: 162.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 0.625140493602474 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0287 -0.7816  0.0403  0.8678  3.4348 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95832    0.08757 113.722  < 2e-16 ***
## category_code_LT01_1_count   0.37857    0.08546   4.430 1.16e-05 ***
## category_code_LT01_2_count   0.68540    0.08659   7.916 1.64e-14 ***
## category_code_LT01_5_count   0.98900    0.06096  16.225  < 2e-16 ***
## category_code_LT01_11_count  0.38606    0.11831   3.263  0.00118 ** 
## category_code_LT01_12_count -0.15684    0.21231  -0.739  0.46043    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6289, Adjusted R-squared:  0.6251 
## F-statistic: 166.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 0.624725581966173 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0255 -0.7620  0.0455  0.8838  3.4352 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.957947   0.087618 113.652  < 2e-16 ***
## category_code_LT01_1_count  0.373290   0.086201   4.330  1.8e-05 ***
## category_code_LT01_2_count  0.683013   0.086660   7.882  2.1e-14 ***
## category_code_LT01_5_count  0.984897   0.060793  16.201  < 2e-16 ***
## category_code_LT01_11_count 0.366382   0.115440   3.174   0.0016 ** 
## category_code_LT01_13_count 0.008291   0.244732   0.034   0.9730    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.6247 
## F-statistic: 166.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 0.624810157122276 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0253 -0.7736  0.0432  0.8881  3.4337 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95947    0.08773 113.528  < 2e-16 ***
## category_code_LT01_1_count   0.36995    0.08598   4.303 2.04e-05 ***
## category_code_LT01_2_count   0.68042    0.08695   7.825 3.12e-14 ***
## category_code_LT01_5_count   0.98242    0.06122  16.048  < 2e-16 ***
## category_code_LT01_11_count  0.36580    0.11538   3.170  0.00162 ** 
## category_code_LT01_14_count  0.10934    0.32665   0.335  0.73796    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6248 
## F-statistic: 166.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 0.624868041267123 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0247 -0.7467  0.0450  0.8700  3.4360 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95712    0.08762 113.644  < 2e-16 ***
## category_code_LT01_1_count   0.38044    0.08663   4.391 1.38e-05 ***
## category_code_LT01_2_count   0.68495    0.08667   7.903 1.80e-14 ***
## category_code_LT01_5_count   0.98487    0.06073  16.216  < 2e-16 ***
## category_code_LT01_11_count  0.36754    0.11538   3.186  0.00154 ** 
## category_code_LT01_15_count -0.32886    0.75847  -0.434  0.66479    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6249 
## F-statistic: 166.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 0.624810183534469 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0255 -0.7607  0.0476  0.8891  3.4350 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95819    0.08761 113.668  < 2e-16 ***
## category_code_LT01_1_count   0.37469    0.08529   4.393 1.37e-05 ***
## category_code_LT01_2_count   0.67975    0.08716   7.799 3.77e-14 ***
## category_code_LT01_5_count   0.98460    0.06075  16.208  < 2e-16 ***
## category_code_LT01_11_count  0.36684    0.11536   3.180  0.00157 ** 
## category_code_LT01_16_count  0.39050    1.16638   0.335  0.73792    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6248 
## F-statistic: 166.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 0.617042443932189 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0257 -0.7982  0.0045  0.8853  3.4488 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.944332   0.088405  112.49  < 2e-16 ***
## category_code_LT01_1_count   0.446454   0.084722    5.27 2.05e-07 ***
## category_code_LT01_2_count   0.845701   0.072110   11.73  < 2e-16 ***
## category_code_LT01_5_count   1.004861   0.061460   16.35  < 2e-16 ***
## category_code_LT01_12_count -0.002177   0.209163   -0.01    0.992    
## category_code_LT01_13_count  0.034517   0.247093    0.14    0.889    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.617 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 0.617145996800669 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0257 -0.7943  0.0059  0.8886  3.4471 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.946052   0.088516 112.365  < 2e-16 ***
## category_code_LT01_1_count   0.444012   0.084351   5.264 2.11e-07 ***
## category_code_LT01_2_count   0.843218   0.072376  11.650  < 2e-16 ***
## category_code_LT01_5_count   1.002313   0.061847  16.206  < 2e-16 ***
## category_code_LT01_12_count -0.006979   0.209527  -0.033    0.973    
## category_code_LT01_14_count  0.129121   0.330545   0.391    0.696    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6171 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 0.617131032622384 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0252 -0.8003  0.0161  0.8793  3.4497 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.943472   0.088412 112.468  < 2e-16 ***
## category_code_LT01_1_count   0.454432   0.085261   5.330  1.5e-07 ***
## category_code_LT01_2_count   0.848611   0.072148  11.762  < 2e-16 ***
## category_code_LT01_5_count   1.005280   0.061399  16.373  < 2e-16 ***
## category_code_LT01_12_count -0.005221   0.209326  -0.025    0.980    
## category_code_LT01_15_count -0.280024   0.766808  -0.365    0.715    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6171 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 0.617099721354573 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0258 -0.7976  0.0064  0.8896  3.4487 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.944438   0.088397 112.498  < 2e-16 ***
## category_code_LT01_1_count   0.449250   0.083674   5.369 1.22e-07 ***
## category_code_LT01_2_count   0.843394   0.072599  11.617  < 2e-16 ***
## category_code_LT01_5_count   1.004863   0.061412  16.363  < 2e-16 ***
## category_code_LT01_12_count -0.001013   0.209161  -0.005    0.996    
## category_code_LT01_16_count  0.359579   1.178383   0.305    0.760    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6171 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 0.617161430747486 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0254 -0.7938  0.0069  0.8908  3.4469 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94621    0.08852 112.361  < 2e-16 ***
## category_code_LT01_1_count   0.44164    0.08476   5.211 2.77e-07 ***
## category_code_LT01_2_count   0.84194    0.07121  11.823  < 2e-16 ***
## category_code_LT01_5_count   1.00171    0.06158  16.266  < 2e-16 ***
## category_code_LT01_13_count  0.03576    0.24707   0.145    0.885    
## category_code_LT01_14_count  0.12906    0.32994   0.391    0.696    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6172 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 0.617139499915256 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0250 -0.7987  0.0124  0.8811  3.4495 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94361    0.08842 112.463  < 2e-16 ***
## category_code_LT01_1_count   0.45249    0.08570   5.280 1.94e-07 ***
## category_code_LT01_2_count   0.84760    0.07085  11.963  < 2e-16 ***
## category_code_LT01_5_count   1.00483    0.06108  16.452  < 2e-16 ***
## category_code_LT01_13_count  0.02661    0.24806   0.107    0.915    
## category_code_LT01_15_count -0.27177    0.76921  -0.353    0.724    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6171 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617117445561659 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0257 -0.7971  0.0063  0.8921  3.4486 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94460    0.08840 112.496  < 2e-16 ***
## category_code_LT01_1_count   0.44715    0.08395   5.326 1.53e-07 ***
## category_code_LT01_2_count   0.84244    0.07132  11.812  < 2e-16 ***
## category_code_LT01_5_count   1.00443    0.06109  16.442  < 2e-16 ***
## category_code_LT01_13_count  0.03733    0.24723   0.151    0.880    
## category_code_LT01_16_count  0.36623    1.17904   0.311    0.756    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6171 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 0.617246943035735 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0248 -0.7933  0.0215  0.8862  3.4478 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94534    0.08853 112.343  < 2e-16 ***
## category_code_LT01_1_count   0.44951    0.08517   5.278 1.96e-07 ***
## category_code_LT01_2_count   0.84469    0.07118  11.866  < 2e-16 ***
## category_code_LT01_5_count   1.00208    0.06151  16.290  < 2e-16 ***
## category_code_LT01_14_count  0.12760    0.32988   0.387    0.699    
## category_code_LT01_15_count -0.27711    0.76600  -0.362    0.718    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6172 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617228291457265 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0255 -0.7939  0.0076  0.8961  3.4468 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94640    0.08851 112.373  < 2e-16 ***
## category_code_LT01_1_count   0.44445    0.08365   5.313 1.64e-07 ***
## category_code_LT01_2_count   0.83938    0.07173  11.702  < 2e-16 ***
## category_code_LT01_5_count   1.00161    0.06153  16.277  < 2e-16 ***
## category_code_LT01_14_count  0.13431    0.33037   0.407    0.685    
## category_code_LT01_16_count  0.38572    1.17981   0.327    0.744    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6172 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617197791479482 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0251 -0.7982  0.0174  0.8853  3.4494 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94374    0.08841 112.477  < 2e-16 ***
## category_code_LT01_1_count   0.45489    0.08438   5.391 1.09e-07 ***
## category_code_LT01_2_count   0.84531    0.07129  11.857  < 2e-16 ***
## category_code_LT01_5_count   1.00480    0.06103  16.465  < 2e-16 ***
## category_code_LT01_15_count -0.27212    0.76641  -0.355    0.723    
## category_code_LT01_16_count  0.34651    1.17869   0.294    0.769    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6172 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 0.629891446524928 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9729 -0.7402  0.0587  0.9013  3.4736 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95065    0.08685 114.572  < 2e-16 ***
## category_code_LT01_1_count  0.25318    0.08851   2.860  0.00441 ** 
## category_code_LT01_3_count  0.30617    0.11271   2.716  0.00683 ** 
## category_code_LT01_4_count  0.73809    0.09231   7.996 9.27e-15 ***
## category_code_LT01_5_count  0.91957    0.06179  14.882  < 2e-16 ***
## category_code_LT01_6_count  0.42197    0.14957   2.821  0.00498 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 492 degrees of freedom
## Multiple R-squared:  0.6336, Adjusted R-squared:  0.6299 
## F-statistic: 170.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 0.630739361166809 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9949 -0.7507  0.0240  0.8594  3.4485 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96709    0.08660 115.094  < 2e-16 ***
## category_code_LT01_1_count  0.24792    0.08852   2.801  0.00530 ** 
## category_code_LT01_3_count  0.32589    0.11203   2.909  0.00379 ** 
## category_code_LT01_4_count  0.72989    0.09251   7.890 1.97e-14 ***
## category_code_LT01_5_count  0.92751    0.06145  15.094  < 2e-16 ***
## category_code_LT01_7_count  0.46012    0.15247   3.018  0.00268 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 492 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:  0.6307 
## F-statistic: 170.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 0.624212318992387 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0067 -0.7670  0.0229  0.8452  3.4295 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96672    0.08739 114.047  < 2e-16 ***
## category_code_LT01_1_count  0.27362    0.08898   3.075  0.00222 ** 
## category_code_LT01_3_count  0.34166    0.11293   3.025  0.00261 ** 
## category_code_LT01_4_count  0.81191    0.08919   9.103  < 2e-16 ***
## category_code_LT01_5_count  0.94517    0.06258  15.103  < 2e-16 ***
## category_code_LT01_8_count -0.17369    0.27343  -0.635  0.52558    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 492 degrees of freedom
## Multiple R-squared:  0.628,  Adjusted R-squared:  0.6242 
## F-statistic: 166.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 0.626366236949272 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9914 -0.7507  0.0435  0.8920  3.4506 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96115    0.08714 114.314  < 2e-16 ***
## category_code_LT01_1_count  0.26591    0.08875   2.996  0.00287 ** 
## category_code_LT01_3_count  0.30902    0.11393   2.712  0.00691 ** 
## category_code_LT01_4_count  0.79728    0.08931   8.927  < 2e-16 ***
## category_code_LT01_5_count  0.93102    0.06185  15.052  < 2e-16 ***
## category_code_LT01_9_count  0.40565    0.22529   1.801  0.07238 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6264 
## F-statistic: 167.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 0.624786205996205 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9748 -0.7687  0.0064  0.8803  3.3300 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93898    0.09064 109.654  < 2e-16 ***
## category_code_LT01_1_count   0.27535    0.08893   3.096  0.00207 ** 
## category_code_LT01_3_count   0.31703    0.11490   2.759  0.00601 ** 
## category_code_LT01_4_count   0.80542    0.08933   9.016  < 2e-16 ***
## category_code_LT01_5_count   0.93909    0.06182  15.191  < 2e-16 ***
## category_code_LT01_10_count  0.12189    0.11334   1.075  0.28269    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6248 
## F-statistic: 166.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 0.630985237117937 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0037 -0.7636  0.0431  0.8734  3.4385 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97401    0.08662 115.152  < 2e-16 ***
## category_code_LT01_1_count   0.22776    0.08930   2.551  0.01106 *  
## category_code_LT01_3_count   0.25395    0.11537   2.201  0.02819 *  
## category_code_LT01_4_count   0.68454    0.09764   7.011 7.85e-12 ***
## category_code_LT01_5_count   0.93026    0.06138  15.157  < 2e-16 ***
## category_code_LT01_11_count  0.34945    0.11373   3.073  0.00224 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 492 degrees of freedom
## Multiple R-squared:  0.6347, Adjusted R-squared:  0.631 
## F-statistic:   171 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 0.624000380003177 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9994 -0.7547  0.0174  0.8662  3.4401 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96514    0.08738 114.038  < 2e-16 ***
## category_code_LT01_1_count   0.26814    0.08961   2.992  0.00291 ** 
## category_code_LT01_3_count   0.33766    0.11321   2.983  0.00300 ** 
## category_code_LT01_4_count   0.80872    0.08971   9.015  < 2e-16 ***
## category_code_LT01_5_count   0.93691    0.06221  15.060  < 2e-16 ***
## category_code_LT01_12_count  0.07309    0.20595   0.355  0.72281    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 492 degrees of freedom
## Multiple R-squared:  0.6278, Adjusted R-squared:  0.624 
## F-statistic:   166 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 0.623910557733028 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0010 -0.7581  0.0347  0.8452  3.4377 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96530    0.08740 114.022  < 2e-16 ***
## category_code_LT01_1_count   0.27082    0.08984   3.014  0.00271 ** 
## category_code_LT01_3_count   0.34040    0.11296   3.014  0.00271 ** 
## category_code_LT01_4_count   0.81148    0.08944   9.072  < 2e-16 ***
## category_code_LT01_5_count   0.93897    0.06193  15.162  < 2e-16 ***
## category_code_LT01_13_count  0.02248    0.24493   0.092  0.92690    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 492 degrees of freedom
## Multiple R-squared:  0.6277, Adjusted R-squared:  0.6239 
## F-statistic: 165.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 0.623954261377989 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0009 -0.7579  0.0251  0.8602  3.4384 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96634    0.08750 113.904  < 2e-16 ***
## category_code_LT01_1_count   0.26948    0.08949   3.011  0.00274 ** 
## category_code_LT01_3_count   0.34199    0.11312   3.023  0.00263 ** 
## category_code_LT01_4_count   0.80834    0.09039   8.943  < 2e-16 ***
## category_code_LT01_5_count   0.93734    0.06230  15.046  < 2e-16 ***
## category_code_LT01_14_count  0.08417    0.32862   0.256  0.79795    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 492 degrees of freedom
## Multiple R-squared:  0.6277, Adjusted R-squared:  0.624 
## F-statistic: 165.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 0.624106850441426 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9997 -0.7569  0.0258  0.8470  3.4391 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96415    0.08740 114.010  < 2e-16 ***
## category_code_LT01_1_count   0.27949    0.09014   3.100  0.00204 ** 
## category_code_LT01_3_count   0.34684    0.11361   3.053  0.00239 ** 
## category_code_LT01_4_count   0.81198    0.08920   9.103  < 2e-16 ***
## category_code_LT01_5_count   0.93876    0.06188  15.171  < 2e-16 ***
## category_code_LT01_15_count -0.39299    0.76291  -0.515  0.60670    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 492 degrees of freedom
## Multiple R-squared:  0.6279, Adjusted R-squared:  0.6241 
## F-statistic:   166 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 0.624344649783696 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0008 -0.7558  0.0227  0.8549  3.4381 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96551    0.08734 114.094  < 2e-16 ***
## category_code_LT01_1_count   0.27407    0.08897   3.081  0.00218 ** 
## category_code_LT01_3_count   0.32929    0.11384   2.893  0.00399 ** 
## category_code_LT01_4_count   0.81223    0.08917   9.109  < 2e-16 ***
## category_code_LT01_5_count   0.93837    0.06186  15.168  < 2e-16 ***
## category_code_LT01_16_count  0.88752    1.16842   0.760  0.44787    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6243 
## F-statistic: 166.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 0.601565597065753 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0366 -0.8248  0.0248  0.9233  3.6653 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97677    0.09004 110.803  < 2e-16 ***
## category_code_LT01_1_count  0.43956    0.08650   5.082 5.33e-07 ***
## category_code_LT01_3_count  0.60465    0.10697   5.652 2.68e-08 ***
## category_code_LT01_5_count  0.97371    0.06345  15.345  < 2e-16 ***
## category_code_LT01_6_count  0.69550    0.14940   4.655 4.17e-06 ***
## category_code_LT01_7_count  0.75080    0.15197   4.940 1.07e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.422 on 492 degrees of freedom
## Multiple R-squared:  0.6056, Adjusted R-squared:  0.6016 
## F-statistic: 151.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 0.604527218368211 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0516 -0.7909  0.0255  0.9265  3.4029 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99024    0.08973 111.335  < 2e-16 ***
## category_code_LT01_1_count   0.38760    0.08836   4.387 1.41e-05 ***
## category_code_LT01_3_count   0.46101    0.11401   4.044 6.11e-05 ***
## category_code_LT01_5_count   0.97600    0.06312  15.462  < 2e-16 ***
## category_code_LT01_6_count   0.55200    0.15340   3.599 0.000352 ***
## category_code_LT01_11_count  0.58639    0.11028   5.317 1.60e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 492 degrees of freedom
## Multiple R-squared:  0.6085, Adjusted R-squared:  0.6045 
## F-statistic: 152.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 0.603593063920546 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0823 -0.8009  0.1123  0.8666  3.3818 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01134    0.08957 111.768  < 2e-16 ***
## category_code_LT01_1_count   0.39083    0.08841   4.421 1.21e-05 ***
## category_code_LT01_3_count   0.50094    0.11316   4.427 1.18e-05 ***
## category_code_LT01_5_count   0.98981    0.06279  15.764  < 2e-16 ***
## category_code_LT01_7_count   0.54949    0.16024   3.429 0.000656 ***
## category_code_LT01_11_count  0.55824    0.11325   4.929 1.13e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 492 degrees of freedom
## Multiple R-squared:  0.6076, Adjusted R-squared:  0.6036 
## F-statistic: 152.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 0.631604353728519 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9860 -0.7521  0.0489  0.8882  3.9004 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96253    0.08657 115.084  < 2e-16 ***
## category_code_LT01_1_count  0.25817    0.08797   2.935  0.00349 ** 
## category_code_LT01_4_count  0.75801    0.08772   8.641  < 2e-16 ***
## category_code_LT01_5_count  0.92133    0.06155  14.968  < 2e-16 ***
## category_code_LT01_6_count  0.46058    0.14837   3.104  0.00202 ** 
## category_code_LT01_7_count  0.47391    0.15216   3.115  0.00195 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 492 degrees of freedom
## Multiple R-squared:  0.6353, Adjusted R-squared:  0.6316 
## F-statistic: 171.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 0.62471107865538 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9992 -0.7673  0.0430  0.9457  3.8810 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96256    0.08740 113.988  < 2e-16 ***
## category_code_LT01_1_count  0.28605    0.08842   3.235  0.00130 ** 
## category_code_LT01_4_count  0.84693    0.08367  10.122  < 2e-16 ***
## category_code_LT01_5_count  0.94035    0.06268  15.002  < 2e-16 ***
## category_code_LT01_6_count  0.46954    0.14984   3.134  0.00183 ** 
## category_code_LT01_8_count -0.19054    0.27339  -0.697  0.48616    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.6247 
## F-statistic: 166.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 0.627482610292706 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9812 -0.7994  0.0525  0.9245  3.8956 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95585    0.08709 114.323  < 2e-16 ***
## category_code_LT01_1_count  0.27479    0.08818   3.116  0.00194 ** 
## category_code_LT01_4_count  0.82154    0.08432   9.744  < 2e-16 ***
## category_code_LT01_5_count  0.92393    0.06196  14.912  < 2e-16 ***
## category_code_LT01_6_count  0.44493    0.14953   2.975  0.00307 ** 
## category_code_LT01_9_count  0.45391    0.22282   2.037  0.04217 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6312, Adjusted R-squared:  0.6275 
## F-statistic: 168.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 0.625282201236564 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9664 -0.7728  0.0580  0.9588  3.7711 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93413    0.09059 109.660  < 2e-16 ***
## category_code_LT01_1_count   0.28669    0.08834   3.245  0.00125 ** 
## category_code_LT01_4_count   0.83718    0.08410   9.954  < 2e-16 ***
## category_code_LT01_5_count   0.93397    0.06195  15.077  < 2e-16 ***
## category_code_LT01_6_count   0.43683    0.15186   2.876  0.00420 ** 
## category_code_LT01_10_count  0.12551    0.11288   1.112  0.26672    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6253 
## F-statistic: 166.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 0.632096932008251 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9954 -0.7590  0.0698  0.8826  3.6603 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96982    0.08655 115.190  < 2e-16 ***
## category_code_LT01_1_count   0.23356    0.08891   2.627  0.00889 ** 
## category_code_LT01_4_count   0.69919    0.09476   7.379 6.85e-13 ***
## category_code_LT01_5_count   0.92426    0.06145  15.040  < 2e-16 ***
## category_code_LT01_6_count   0.37952    0.15065   2.519  0.01208 *  
## category_code_LT01_11_count  0.36043    0.11191   3.221  0.00136 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.366 on 492 degrees of freedom
## Multiple R-squared:  0.6358, Adjusted R-squared:  0.6321 
## F-statistic: 171.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 0.624368139545266 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9925 -0.7652  0.0530  0.9470  3.8852 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96103    0.08741 113.955  < 2e-16 ***
## category_code_LT01_1_count   0.28226    0.08907   3.169  0.00162 ** 
## category_code_LT01_4_count   0.84569    0.08416  10.049  < 2e-16 ***
## category_code_LT01_5_count   0.93277    0.06230  14.972  < 2e-16 ***
## category_code_LT01_6_count   0.46229    0.15089   3.064  0.00231 ** 
## category_code_LT01_12_count  0.03931    0.20685   0.190  0.84936    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6244 
## F-statistic: 166.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 0.624360831429201 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9931 -0.7662  0.0463  0.9448  3.8851 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96112    0.08742 113.951  < 2e-16 ***
## category_code_LT01_1_count   0.28223    0.08932   3.160  0.00168 ** 
## category_code_LT01_4_count   0.84621    0.08400  10.074  < 2e-16 ***
## category_code_LT01_5_count   0.93350    0.06207  15.040  < 2e-16 ***
## category_code_LT01_6_count   0.46626    0.14984   3.112  0.00197 ** 
## category_code_LT01_13_count  0.03989    0.24485   0.163  0.87065    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6244 
## F-statistic: 166.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 0.624459614476696 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9927 -0.7621  0.0540  0.9487  3.8849 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96261    0.08750 113.864  < 2e-16 ***
## category_code_LT01_1_count   0.28042    0.08895   3.152  0.00172 ** 
## category_code_LT01_4_count   0.84136    0.08506   9.892  < 2e-16 ***
## category_code_LT01_5_count   0.93090    0.06248  14.900  < 2e-16 ***
## category_code_LT01_6_count   0.47149    0.15050   3.133  0.00183 ** 
## category_code_LT01_14_count  0.13011    0.32946   0.395  0.69307    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6245 
## F-statistic: 166.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 0.62441129147113 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9926 -0.7581  0.0522  0.9417  3.8811 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96045    0.08743 113.930  < 2e-16 ***
## category_code_LT01_1_count   0.28903    0.08978   3.219  0.00137 ** 
## category_code_LT01_4_count   0.84839    0.08377  10.128  < 2e-16 ***
## category_code_LT01_5_count   0.93376    0.06202  15.056  < 2e-16 ***
## category_code_LT01_6_count   0.46753    0.14992   3.119  0.00192 ** 
## category_code_LT01_15_count -0.23090    0.75858  -0.304  0.76097    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6244 
## F-statistic: 166.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 0.62569131689879 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9904 -0.7601  0.0532  0.9583  3.8839 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96030    0.08726 114.146  < 2e-16 ***
## category_code_LT01_1_count   0.28520    0.08827   3.231  0.00132 ** 
## category_code_LT01_4_count   0.83770    0.08387   9.988  < 2e-16 ***
## category_code_LT01_5_count   0.93084    0.06195  15.025  < 2e-16 ***
## category_code_LT01_6_count   0.47769    0.14981   3.189  0.00152 ** 
## category_code_LT01_16_count  1.54394    1.15871   1.332  0.18332    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 492 degrees of freedom
## Multiple R-squared:  0.6295, Adjusted R-squared:  0.6257 
## F-statistic: 167.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 0.624735239148689 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0256 -0.7711  0.0106  0.8776  3.8633 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.98157    0.08722 114.439   <2e-16 ***
## category_code_LT01_1_count  0.28420    0.08847   3.212   0.0014 ** 
## category_code_LT01_4_count  0.85196    0.08307  10.256   <2e-16 ***
## category_code_LT01_5_count  0.95096    0.06238  15.246   <2e-16 ***
## category_code_LT01_7_count  0.48220    0.15363   3.139   0.0018 ** 
## category_code_LT01_8_count -0.18433    0.27331  -0.674   0.5003    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.6247 
## F-statistic: 166.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 0.627199518178657 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0072 -0.7645  0.0300  0.8494  3.8777 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97420    0.08695 114.710  < 2e-16 ***
## category_code_LT01_1_count  0.27413    0.08825   3.106  0.00200 ** 
## category_code_LT01_4_count  0.82955    0.08363   9.920  < 2e-16 ***
## category_code_LT01_5_count  0.93499    0.06166  15.163  < 2e-16 ***
## category_code_LT01_7_count  0.44800    0.15391   2.911  0.00377 ** 
## category_code_LT01_9_count  0.43073    0.22362   1.926  0.05466 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.631,  Adjusted R-squared:  0.6272 
## F-statistic: 168.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 0.625789321538821 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9849 -0.7648  0.0290  0.8643  3.7322 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94613    0.09056 109.834  < 2e-16 ***
## category_code_LT01_1_count   0.28453    0.08832   3.222  0.00136 ** 
## category_code_LT01_4_count   0.83625    0.08378   9.982  < 2e-16 ***
## category_code_LT01_5_count   0.94343    0.06158  15.320  < 2e-16 ***
## category_code_LT01_7_count   0.46062    0.15395   2.992  0.00291 ** 
## category_code_LT01_10_count  0.15144    0.11158   1.357  0.17534    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 492 degrees of freedom
## Multiple R-squared:  0.6296, Adjusted R-squared:  0.6258 
## F-statistic: 167.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 0.631329069113283 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0174 -0.7745  0.0318  0.8497  3.6535 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98494    0.08643 115.521  < 2e-16 ***
## category_code_LT01_1_count   0.23587    0.08898   2.651  0.00829 ** 
## category_code_LT01_4_count   0.71518    0.09384   7.621  1.3e-13 ***
## category_code_LT01_5_count   0.93433    0.06121  15.264  < 2e-16 ***
## category_code_LT01_7_count   0.36176    0.15702   2.304  0.02164 *  
## category_code_LT01_11_count  0.34614    0.11373   3.043  0.00246 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 492 degrees of freedom
## Multiple R-squared:  0.635,  Adjusted R-squared:  0.6313 
## F-statistic: 171.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 0.624613399162834 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0167 -0.7692  0.0144  0.8690  3.8708 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97963    0.08720 114.441  < 2e-16 ***
## category_code_LT01_1_count   0.27621    0.08919   3.097  0.00207 ** 
## category_code_LT01_4_count   0.84555    0.08397  10.069  < 2e-16 ***
## category_code_LT01_5_count   0.94095    0.06204  15.167  < 2e-16 ***
## category_code_LT01_7_count   0.47870    0.15359   3.117  0.00194 ** 
## category_code_LT01_12_count  0.11151    0.20530   0.543  0.58725    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6284, Adjusted R-squared:  0.6246 
## F-statistic: 166.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 0.624433038002255 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0197 -0.7693  0.0146  0.8685  3.8644 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97974    0.08723 114.413  < 2e-16 ***
## category_code_LT01_1_count   0.28527    0.08923   3.197  0.00148 ** 
## category_code_LT01_4_count   0.85295    0.08316  10.256  < 2e-16 ***
## category_code_LT01_5_count   0.94504    0.06171  15.314  < 2e-16 ***
## category_code_LT01_7_count   0.48319    0.15452   3.127  0.00187 ** 
## category_code_LT01_13_count -0.05961    0.24619  -0.242  0.80879    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6244 
## F-statistic: 166.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 0.624395818392793 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0196 -0.7690  0.0149  0.8687  3.8660 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97947    0.08735 114.251  < 2e-16 ***
## category_code_LT01_1_count   0.28330    0.08888   3.188  0.00153 ** 
## category_code_LT01_4_count   0.85320    0.08374  10.188  < 2e-16 ***
## category_code_LT01_5_count   0.94526    0.06204  15.237  < 2e-16 ***
## category_code_LT01_7_count   0.48010    0.15392   3.119  0.00192 ** 
## category_code_LT01_14_count -0.03263    0.32856  -0.099  0.92093    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6244 
## F-statistic: 166.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 0.624389995276741 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0195 -0.7694  0.0168  0.8686  3.8657 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97985    0.08724 114.392  < 2e-16 ***
## category_code_LT01_1_count   0.28323    0.08995   3.149  0.00174 ** 
## category_code_LT01_4_count   0.85246    0.08332  10.231  < 2e-16 ***
## category_code_LT01_5_count   0.94461    0.06169  15.312  < 2e-16 ***
## category_code_LT01_7_count   0.47886    0.15377   3.114  0.00195 ** 
## category_code_LT01_15_count -0.03586    0.75871  -0.047  0.96232    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6244 
## F-statistic: 166.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 0.625356346488493 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0179 -0.7693  0.0207  0.8617  3.8654 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97971    0.08712 114.557  < 2e-16 ***
## category_code_LT01_1_count   0.28382    0.08837   3.212  0.00141 ** 
## category_code_LT01_4_count   0.84627    0.08317  10.176  < 2e-16 ***
## category_code_LT01_5_count   0.94257    0.06164  15.292  < 2e-16 ***
## category_code_LT01_7_count   0.47832    0.15343   3.117  0.00193 ** 
## category_code_LT01_16_count  1.30472    1.15716   1.128  0.26007    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6254 
## F-statistic: 166.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 0.621106589830821 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0181 -0.7890  0.0245  0.9079  3.8609 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97358    0.08769 113.740  < 2e-16 ***
## category_code_LT01_1_count  0.29922    0.08864   3.376 0.000794 ***
## category_code_LT01_4_count  0.91051    0.07951  11.451  < 2e-16 ***
## category_code_LT01_5_count  0.95159    0.06277  15.161  < 2e-16 ***
## category_code_LT01_8_count -0.17907    0.27465  -0.652 0.514721    
## category_code_LT01_9_count  0.50386    0.22431   2.246 0.025130 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 492 degrees of freedom
## Multiple R-squared:  0.6249, Adjusted R-squared:  0.6211 
## F-statistic: 163.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 0.619274995890525 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9907 -0.7709  0.0301  0.9008  3.6854 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93938    0.09132 108.840  < 2e-16 ***
## category_code_LT01_1_count   0.31215    0.08871   3.519 0.000473 ***
## category_code_LT01_4_count   0.92043    0.07961  11.561  < 2e-16 ***
## category_code_LT01_5_count   0.96147    0.06271  15.331  < 2e-16 ***
## category_code_LT01_8_count  -0.16980    0.27525  -0.617 0.537591    
## category_code_LT01_10_count  0.18270    0.11213   1.629 0.103898    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 492 degrees of freedom
## Multiple R-squared:  0.6231, Adjusted R-squared:  0.6193 
## F-statistic: 162.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 0.62753140871905 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0269 -0.7663  0.0256  0.9003  3.6005 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98608    0.08691 114.901  < 2e-16 ***
## category_code_LT01_1_count   0.24772    0.08938   2.771 0.005792 ** 
## category_code_LT01_4_count   0.75546    0.09276   8.144 3.17e-15 ***
## category_code_LT01_5_count   0.94630    0.06219  15.216  < 2e-16 ***
## category_code_LT01_8_count  -0.13277    0.27227  -0.488 0.626014    
## category_code_LT01_11_count  0.40909    0.11085   3.690 0.000249 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6275 
## F-statistic: 168.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 0.617477817600077 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0296 -0.7693  0.0100  0.9288  3.8513 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97973    0.08806 113.328  < 2e-16 ***
## category_code_LT01_1_count   0.30414    0.08966   3.392  0.00075 ***
## category_code_LT01_4_count   0.93673    0.07947  11.788  < 2e-16 ***
## category_code_LT01_5_count   0.95939    0.06319  15.182  < 2e-16 ***
## category_code_LT01_8_count  -0.16452    0.27597  -0.596  0.55135    
## category_code_LT01_12_count  0.11920    0.20735   0.575  0.56563    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6175 
## F-statistic: 161.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 0.617223446786598 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0324 -0.7559 -0.0057  0.9169  3.8469 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98003    0.08809 113.292  < 2e-16 ***
## category_code_LT01_1_count   0.31006    0.08985   3.451 0.000607 ***
## category_code_LT01_4_count   0.94352    0.07877  11.978  < 2e-16 ***
## category_code_LT01_5_count   0.96297    0.06294  15.300  < 2e-16 ***
## category_code_LT01_8_count  -0.15828    0.27646  -0.573 0.567236    
## category_code_LT01_13_count  0.01426    0.24759   0.058 0.954101    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6172 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 0.617228254957208 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0325 -0.7620 -0.0056  0.9255  3.8466 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98045    0.08821 113.142  < 2e-16 ***
## category_code_LT01_1_count   0.30991    0.08940   3.467 0.000573 ***
## category_code_LT01_4_count   0.94271    0.07945  11.865  < 2e-16 ***
## category_code_LT01_5_count   0.96247    0.06324  15.220  < 2e-16 ***
## category_code_LT01_8_count  -0.15959    0.27593  -0.578 0.563290    
## category_code_LT01_14_count  0.03226    0.33108   0.097 0.922409    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6172 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 0.617244994267627 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0322 -0.7589  0.0018  0.9257  3.8448 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97971    0.08810 113.275  < 2e-16 ***
## category_code_LT01_1_count   0.31361    0.09037   3.470 0.000565 ***
## category_code_LT01_4_count   0.94472    0.07865  12.012  < 2e-16 ***
## category_code_LT01_5_count   0.96310    0.06287  15.318  < 2e-16 ***
## category_code_LT01_8_count  -0.15899    0.27591  -0.576 0.564711    
## category_code_LT01_15_count -0.13476    0.76520  -0.176 0.860282    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6172 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 0.618270091515328 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0313 -0.7628  0.0005  0.9268  3.8455 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97991    0.08797 113.449  < 2e-16 ***
## category_code_LT01_1_count   0.31233    0.08883   3.516 0.000478 ***
## category_code_LT01_4_count   0.93760    0.07859  11.931  < 2e-16 ***
## category_code_LT01_5_count   0.96154    0.06280  15.310  < 2e-16 ***
## category_code_LT01_8_count  -0.17551    0.27589  -0.636 0.524968    
## category_code_LT01_16_count  1.36004    1.16954   1.163 0.245438    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6183 
## F-statistic:   162 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 0.622159429135051 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9786 -0.7706  0.0154  0.8955  3.7295 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93892    0.09096 109.271  < 2e-16 ***
## category_code_LT01_1_count   0.29944    0.08849   3.384 0.000771 ***
## category_code_LT01_4_count   0.89370    0.08038  11.118  < 2e-16 ***
## category_code_LT01_5_count   0.94474    0.06197  15.244  < 2e-16 ***
## category_code_LT01_9_count   0.45947    0.22583   2.035 0.042432 *  
## category_code_LT01_10_count  0.15102    0.11265   1.341 0.180670    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 492 degrees of freedom
## Multiple R-squared:  0.626,  Adjusted R-squared:  0.6222 
## F-statistic: 164.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 0.630107747273319 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0100 -0.7686  0.0476  0.9134  3.6262 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97904    0.08663 115.190  < 2e-16 ***
## category_code_LT01_1_count   0.23922    0.08909   2.685 0.007494 ** 
## category_code_LT01_4_count   0.73542    0.09296   7.911  1.7e-14 ***
## category_code_LT01_5_count   0.93204    0.06143  15.171  < 2e-16 ***
## category_code_LT01_9_count   0.42601    0.22249   1.915 0.056103 .  
## category_code_LT01_11_count  0.39069    0.11091   3.523 0.000467 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 492 degrees of freedom
## Multiple R-squared:  0.6338, Adjusted R-squared:  0.6301 
## F-statistic: 170.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 0.620988159390923 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0096 -0.7788  0.0349  0.9269  3.8681 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97179    0.08767 113.741  < 2e-16 ***
## category_code_LT01_1_count   0.29148    0.08936   3.262  0.00118 ** 
## category_code_LT01_4_count   0.90414    0.08045  11.238  < 2e-16 ***
## category_code_LT01_5_count   0.94196    0.06243  15.089  < 2e-16 ***
## category_code_LT01_9_count   0.49721    0.22426   2.217  0.02707 *  
## category_code_LT01_12_count  0.10744    0.20632   0.521  0.60276    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 492 degrees of freedom
## Multiple R-squared:  0.6248, Adjusted R-squared:  0.621 
## F-statistic: 163.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 0.620824150675702 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0120 -0.7856  0.0320  0.9206  3.8656 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97220    0.08769 113.720  < 2e-16 ***
## category_code_LT01_1_count   0.29437    0.08956   3.287  0.00109 ** 
## category_code_LT01_4_count   0.90870    0.07988  11.376  < 2e-16 ***
## category_code_LT01_5_count   0.94483    0.06214  15.206  < 2e-16 ***
## category_code_LT01_9_count   0.50274    0.22477   2.237  0.02575 *  
## category_code_LT01_13_count  0.05950    0.24647   0.241  0.80934    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 492 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:  0.6208 
## F-statistic: 163.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 0.620781159966836 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0123 -0.7905  0.0307  0.9172  3.8636 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97181    0.08783 113.542  < 2e-16 ***
## category_code_LT01_1_count   0.29791    0.08906   3.345 0.000886 ***
## category_code_LT01_4_count   0.91104    0.08033  11.341  < 2e-16 ***
## category_code_LT01_5_count   0.94578    0.06242  15.151  < 2e-16 ***
## category_code_LT01_9_count   0.49988    0.22474   2.224 0.026586 *  
## category_code_LT01_14_count -0.01649    0.33018  -0.050 0.960190    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 492 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:  0.6208 
## F-statistic: 163.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 0.620790801937557 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0121 -0.7894  0.0330  0.9181  3.8625 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97186    0.08771 113.697  < 2e-16 ***
## category_code_LT01_1_count   0.29945    0.09008   3.324 0.000953 ***
## category_code_LT01_4_count   0.91110    0.07970  11.431  < 2e-16 ***
## category_code_LT01_5_count   0.94546    0.06208  15.229  < 2e-16 ***
## category_code_LT01_9_count   0.49845    0.22436   2.222 0.026763 *  
## category_code_LT01_15_count -0.09332    0.76189  -0.122 0.902560    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 492 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:  0.6208 
## F-statistic: 163.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 0.621597646110251 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0111 -0.7804  0.0340  0.9183  3.8627 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97200    0.08760 113.837  < 2e-16 ***
## category_code_LT01_1_count   0.29895    0.08855   3.376 0.000794 ***
## category_code_LT01_4_count   0.90563    0.07960  11.377  < 2e-16 ***
## category_code_LT01_5_count   0.94382    0.06204  15.214  < 2e-16 ***
## category_code_LT01_9_count   0.48808    0.22431   2.176 0.030034 *  
## category_code_LT01_16_count  1.20101    1.16427   1.032 0.302789    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6254, Adjusted R-squared:  0.6216 
## F-statistic: 164.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 0.628761250308051 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9876 -0.7539  0.0402  0.8997  3.4749 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95094    0.09023 110.288  < 2e-16 ***
## category_code_LT01_1_count   0.24888    0.08920   2.790  0.00547 ** 
## category_code_LT01_4_count   0.74017    0.09319   7.943 1.35e-14 ***
## category_code_LT01_5_count   0.94036    0.06135  15.328  < 2e-16 ***
## category_code_LT01_10_count  0.15173    0.11100   1.367  0.17227    
## category_code_LT01_11_count  0.39938    0.11093   3.600  0.00035 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.372 on 492 degrees of freedom
## Multiple R-squared:  0.6325, Adjusted R-squared:  0.6288 
## F-statistic: 169.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 0.619152432177193 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9836 -0.7744  0.0383  0.9130  3.6961 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93860    0.09132 108.832  < 2e-16 ***
## category_code_LT01_1_count   0.30487    0.08944   3.409 0.000706 ***
## category_code_LT01_4_count   0.91479    0.08048  11.367  < 2e-16 ***
## category_code_LT01_5_count   0.95238    0.06236  15.273  < 2e-16 ***
## category_code_LT01_10_count  0.17825    0.11228   1.588 0.113030    
## category_code_LT01_12_count  0.09759    0.20708   0.471 0.637655    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 492 degrees of freedom
## Multiple R-squared:  0.623,  Adjusted R-squared:  0.6192 
## F-statistic: 162.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 0.618981777154444 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9855 -0.7744  0.0344  0.9055  3.6900 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.938295   0.091352 108.791  < 2e-16 ***
## category_code_LT01_1_count  0.309876   0.089580   3.459 0.000589 ***
## category_code_LT01_4_count  0.920071   0.079860  11.521  < 2e-16 ***
## category_code_LT01_5_count  0.955477   0.062043  15.400  < 2e-16 ***
## category_code_LT01_10_count 0.180922   0.112208   1.612 0.107520    
## category_code_LT01_13_count 0.009977   0.246668   0.040 0.967752    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 492 degrees of freedom
## Multiple R-squared:  0.6228, Adjusted R-squared:  0.619 
## F-statistic: 162.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 0.619034922094089 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9840 -0.7756  0.0290  0.9021  3.6833 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93550    0.09191 108.103  < 2e-16 ***
## category_code_LT01_1_count   0.31288    0.08919   3.508 0.000493 ***
## category_code_LT01_4_count   0.92277    0.08017  11.509  < 2e-16 ***
## category_code_LT01_5_count   0.95735    0.06237  15.351  < 2e-16 ***
## category_code_LT01_10_count  0.18767    0.11487   1.634 0.102940    
## category_code_LT01_14_count -0.08968    0.33831  -0.265 0.791054    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 492 degrees of freedom
## Multiple R-squared:  0.6229, Adjusted R-squared:  0.619 
## F-statistic: 162.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 0.619060400695338 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9842 -0.7689  0.0319  0.9052  3.6838 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93701    0.09141 108.712  < 2e-16 ***
## category_code_LT01_1_count   0.31556    0.09014   3.501 0.000506 ***
## category_code_LT01_4_count   0.92142    0.07971  11.560  < 2e-16 ***
## category_code_LT01_5_count   0.95549    0.06200  15.412  < 2e-16 ***
## category_code_LT01_10_count  0.18421    0.11256   1.637 0.102362    
## category_code_LT01_15_count -0.24614    0.76626  -0.321 0.748180    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 492 degrees of freedom
## Multiple R-squared:  0.6229, Adjusted R-squared:  0.6191 
## F-statistic: 162.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 0.619839126657912 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9853 -0.7605  0.0343  0.9109  3.6942 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93936    0.09124 108.935  < 2e-16 ***
## category_code_LT01_1_count   0.31158    0.08860   3.517 0.000477 ***
## category_code_LT01_4_count   0.91536    0.07969  11.486  < 2e-16 ***
## category_code_LT01_5_count   0.95368    0.06196  15.392  < 2e-16 ***
## category_code_LT01_10_count  0.17510    0.11216   1.561 0.119146    
## category_code_LT01_16_count  1.23032    1.16713   1.054 0.292336    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6198 
## F-statistic: 163.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 0.627469920989951 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0245 -0.7700  0.0259  0.8923  3.5914 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98532    0.08689 114.918  < 2e-16 ***
## category_code_LT01_1_count   0.24906    0.08964   2.779 0.005669 ** 
## category_code_LT01_4_count   0.75426    0.09275   8.132 3.47e-15 ***
## category_code_LT01_5_count   0.94392    0.06172  15.292  < 2e-16 ***
## category_code_LT01_11_count  0.42209    0.11462   3.683 0.000256 ***
## category_code_LT01_12_count -0.08369    0.21152  -0.396 0.692517    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6312, Adjusted R-squared:  0.6275 
## F-statistic: 168.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 0.627352103373589 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0225 -0.7644  0.0250  0.9048  3.6015 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.984895   0.086902 114.899  < 2e-16 ***
## category_code_LT01_1_count   0.246496   0.090126   2.735 0.006463 ** 
## category_code_LT01_4_count   0.754688   0.092878   8.126 3.63e-15 ***
## category_code_LT01_5_count   0.941677   0.061493  15.314  < 2e-16 ***
## category_code_LT01_11_count  0.410628   0.110902   3.703 0.000238 ***
## category_code_LT01_13_count -0.007545   0.243950  -0.031 0.975340    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6311, Adjusted R-squared:  0.6274 
## F-statistic: 168.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 0.627354295246091 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0225 -0.7646  0.0255  0.9070  3.6019 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98520    0.08702 114.749  < 2e-16 ***
## category_code_LT01_1_count   0.24558    0.08978   2.735 0.006454 ** 
## category_code_LT01_4_count   0.75382    0.09349   8.063 5.71e-15 ***
## category_code_LT01_5_count   0.94119    0.06183  15.223  < 2e-16 ***
## category_code_LT01_11_count  0.41046    0.11084   3.703 0.000237 ***
## category_code_LT01_14_count  0.02027    0.32666   0.062 0.950547    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6311, Adjusted R-squared:  0.6274 
## F-statistic: 168.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 0.627422832426982 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0219 -0.7639  0.0257  0.8997  3.5982 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98445    0.08690 114.891  < 2e-16 ***
## category_code_LT01_1_count   0.25081    0.09063   2.767 0.005862 ** 
## category_code_LT01_4_count   0.75544    0.09280   8.140 3.26e-15 ***
## category_code_LT01_5_count   0.94153    0.06145  15.321  < 2e-16 ***
## category_code_LT01_11_count  0.41166    0.11089   3.712 0.000229 ***
## category_code_LT01_15_count -0.23203    0.75538  -0.307 0.758840    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6312, Adjusted R-squared:  0.6274 
## F-statistic: 168.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 0.62808182541905 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0211 -0.7638  0.0335  0.8948  3.6041 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98466    0.08681 115.012  < 2e-16 ***
## category_code_LT01_1_count   0.24802    0.08928   2.778  0.00568 ** 
## category_code_LT01_4_count   0.75150    0.09273   8.105 4.23e-15 ***
## category_code_LT01_5_count   0.94000    0.06142  15.305  < 2e-16 ***
## category_code_LT01_11_count  0.40566    0.11084   3.660  0.00028 ***
## category_code_LT01_16_count  1.13445    1.15407   0.983  0.32609    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 492 degrees of freedom
## Multiple R-squared:  0.6318, Adjusted R-squared:  0.6281 
## F-statistic: 168.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 0.617207432756542 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0242 -0.7679  0.0035  0.9326  3.8545 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97834    0.08806 113.310  < 2e-16 ***
## category_code_LT01_1_count   0.30158    0.09052   3.332 0.000928 ***
## category_code_LT01_4_count   0.93611    0.07974  11.740  < 2e-16 ***
## category_code_LT01_5_count   0.95359    0.06255  15.246  < 2e-16 ***
## category_code_LT01_12_count  0.11491    0.20733   0.554 0.579671    
## category_code_LT01_13_count  0.02157    0.24712   0.087 0.930475    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6172 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 0.617203909949136 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0243 -0.7681  0.0034  0.9356  3.8539 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97853    0.08818 113.157  < 2e-16 ***
## category_code_LT01_1_count   0.30220    0.09005   3.356 0.000852 ***
## category_code_LT01_4_count   0.93602    0.08031  11.655  < 2e-16 ***
## category_code_LT01_5_count   0.95342    0.06284  15.172  < 2e-16 ***
## category_code_LT01_12_count  0.11438    0.20773   0.551 0.582144    
## category_code_LT01_14_count  0.01845    0.33174   0.056 0.955678    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6172 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 0.617221214919822 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0240 -0.7676  0.0022  0.9351  3.8523 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97802    0.08807 113.295  < 2e-16 ***
## category_code_LT01_1_count   0.30529    0.09116   3.349 0.000873 ***
## category_code_LT01_4_count   0.93748    0.07966  11.768  < 2e-16 ***
## category_code_LT01_5_count   0.95380    0.06251  15.259  < 2e-16 ***
## category_code_LT01_12_count  0.11390    0.20745   0.549 0.583207    
## category_code_LT01_15_count -0.12188    0.76573  -0.159 0.873601    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6172 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 0.618192728047053 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0226 -0.7676  0.0063  0.9404  3.8531 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97806    0.08795 113.458  < 2e-16 ***
## category_code_LT01_1_count   0.30404    0.08955   3.395 0.000741 ***
## category_code_LT01_4_count   0.93056    0.07958  11.694  < 2e-16 ***
## category_code_LT01_5_count   0.95172    0.06246  15.238  < 2e-16 ***
## category_code_LT01_12_count  0.11433    0.20705   0.552 0.581062    
## category_code_LT01_16_count  1.32023    1.16816   1.130 0.258952    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6182 
## F-statistic: 161.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616975065112126 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0271 -0.7686 -0.0018  0.9181  3.8499 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97908    0.08821 113.129  < 2e-16 ***
## category_code_LT01_1_count   0.30711    0.09028   3.402 0.000725 ***
## category_code_LT01_4_count   0.94185    0.07975  11.810  < 2e-16 ***
## category_code_LT01_5_count   0.95673    0.06258  15.289  < 2e-16 ***
## category_code_LT01_13_count  0.02351    0.24721   0.095 0.924262    
## category_code_LT01_14_count  0.03055    0.33120   0.092 0.926538    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.617 
## F-statistic: 161.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616991404477936 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0268 -0.7679 -0.0055  0.9189  3.8480 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97836    0.08810 113.260  < 2e-16 ***
## category_code_LT01_1_count   0.31092    0.09144   3.400 0.000728 ***
## category_code_LT01_4_count   0.94390    0.07897  11.953  < 2e-16 ***
## category_code_LT01_5_count   0.95738    0.06219  15.393  < 2e-16 ***
## category_code_LT01_13_count  0.01936    0.24816   0.078 0.937836    
## category_code_LT01_15_count -0.13199    0.76849  -0.172 0.863702    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.617 
## F-statistic: 161.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617969145982893 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0254 -0.7680  0.0028  0.9195  3.8493 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97846    0.08797 113.427  < 2e-16 ***
## category_code_LT01_1_count   0.30885    0.08969   3.443 0.000624 ***
## category_code_LT01_4_count   0.93659    0.07889  11.872  < 2e-16 ***
## category_code_LT01_5_count   0.95518    0.06214  15.370  < 2e-16 ***
## category_code_LT01_13_count  0.03202    0.24698   0.130 0.896906    
## category_code_LT01_16_count  1.32719    1.16908   1.135 0.256829    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.618 
## F-statistic: 161.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616992913899292 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0269 -0.7683 -0.0051  0.9318  3.8475 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97871    0.08822 113.114  < 2e-16 ***
## category_code_LT01_1_count   0.31120    0.09082   3.427 0.000662 ***
## category_code_LT01_4_count   0.94333    0.07962  11.848  < 2e-16 ***
## category_code_LT01_5_count   0.95694    0.06253  15.303  < 2e-16 ***
## category_code_LT01_14_count  0.02967    0.33116   0.090 0.928644    
## category_code_LT01_15_count -0.13688    0.76546  -0.179 0.858155    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.617 
## F-statistic: 161.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617972225466167 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0255 -0.7686  0.0033  0.9335  3.8485 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97903    0.08809 113.282  < 2e-16 ***
## category_code_LT01_1_count   0.30918    0.08927   3.463  0.00058 ***
## category_code_LT01_4_count   0.93564    0.07960  11.754  < 2e-16 ***
## category_code_LT01_5_count   0.95448    0.06249  15.274  < 2e-16 ***
## category_code_LT01_14_count  0.04772    0.33110   0.144  0.88546    
## category_code_LT01_16_count  1.33030    1.16978   1.137  0.25600    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.618 
## F-statistic: 161.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617973913271313 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0253 -0.7677  0.0013  0.9336  3.8469 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97812    0.08798 113.409  < 2e-16 ***
## category_code_LT01_1_count   0.31290    0.09024   3.467 0.000572 ***
## category_code_LT01_4_count   0.93817    0.07877  11.911  < 2e-16 ***
## category_code_LT01_5_count   0.95547    0.06210  15.386  < 2e-16 ***
## category_code_LT01_15_count -0.11584    0.76470  -0.151 0.879660    
## category_code_LT01_16_count  1.31798    1.16885   1.128 0.260045    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.618 
## F-statistic: 161.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 0.601713862370199 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0820 -0.8093  0.0209  0.9661  3.4229 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01145    0.08982 111.455  < 2e-16 ***
## category_code_LT01_1_count   0.42074    0.08754   4.806 2.05e-06 ***
## category_code_LT01_5_count   0.98918    0.06306  15.687  < 2e-16 ***
## category_code_LT01_6_count   0.63209    0.15248   4.145 4.00e-05 ***
## category_code_LT01_7_count   0.57326    0.16048   3.572 0.000389 ***
## category_code_LT01_11_count  0.61950    0.10927   5.670 2.44e-08 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.421 on 492 degrees of freedom
## Multiple R-squared:  0.6057, Adjusted R-squared:  0.6017 
## F-statistic: 151.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 0.642685744844765 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9510 -0.7379  0.0446  0.8661  3.5037 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94264    0.08517 116.744  < 2e-16 ***
## category_code_LT01_2_count  0.46619    0.09127   5.108 4.67e-07 ***
## category_code_LT01_3_count  0.22569    0.11239   2.008   0.0452 *  
## category_code_LT01_4_count  0.58308    0.09761   5.973 4.46e-09 ***
## category_code_LT01_5_count  0.89952    0.06052  14.863  < 2e-16 ***
## category_code_LT01_6_count  0.28770    0.15013   1.916   0.0559 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 492 degrees of freedom
## Multiple R-squared:  0.6463, Adjusted R-squared:  0.6427 
## F-statistic: 179.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 0.644951080634143 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9637 -0.6968  0.0141  0.8424  3.4895 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95284    0.08480 117.375  < 2e-16 ***
## category_code_LT01_2_count  0.47290    0.08961   5.277 1.97e-07 ***
## category_code_LT01_3_count  0.23331    0.11181   2.087  0.03744 *  
## category_code_LT01_4_count  0.55587    0.09851   5.643 2.83e-08 ***
## category_code_LT01_5_count  0.90314    0.06010  15.027  < 2e-16 ***
## category_code_LT01_7_count  0.39279    0.15024   2.614  0.00921 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 492 degrees of freedom
## Multiple R-squared:  0.6485, Adjusted R-squared:  0.645 
## F-statistic: 181.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 0.64020209024869 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9717 -0.7393  0.0648  0.8675  3.4765 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95204    0.08540 116.538  < 2e-16 ***
## category_code_LT01_2_count  0.50370    0.08940   5.634 2.97e-08 ***
## category_code_LT01_3_count  0.24146    0.11256   2.145   0.0324 *  
## category_code_LT01_4_count  0.61611    0.09649   6.385 3.96e-10 ***
## category_code_LT01_5_count  0.91574    0.06111  14.986  < 2e-16 ***
## category_code_LT01_8_count -0.13399    0.26744  -0.501   0.6166    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.6438, Adjusted R-squared:  0.6402 
## F-statistic: 177.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 0.641353388823666 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9610 -0.7365  0.0413  0.8692  3.4911 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94835    0.08524 116.713  < 2e-16 ***
## category_code_LT01_2_count  0.49103    0.08978   5.469 7.20e-08 ***
## category_code_LT01_3_count  0.21997    0.11333   1.941   0.0528 .  
## category_code_LT01_4_count  0.61069    0.09639   6.336 5.33e-10 ***
## category_code_LT01_5_count  0.90574    0.06046  14.981  < 2e-16 ***
## category_code_LT01_9_count  0.30022    0.22186   1.353   0.1766    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 492 degrees of freedom
## Multiple R-squared:  0.645,  Adjusted R-squared:  0.6414 
## F-statistic: 178.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 0.640293032529895 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9530 -0.7261  0.0416  0.8648  3.4222 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93655    0.08842 112.374  < 2e-16 ***
## category_code_LT01_2_count   0.50049    0.08959   5.587 3.84e-08 ***
## category_code_LT01_3_count   0.22848    0.11411   2.002   0.0458 *  
## category_code_LT01_4_count   0.61478    0.09647   6.373 4.28e-10 ***
## category_code_LT01_5_count   0.91113    0.06042  15.081  < 2e-16 ***
## category_code_LT01_10_count  0.06811    0.11115   0.613   0.5403    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.6439, Adjusted R-squared:  0.6403 
## F-statistic: 177.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 0.642096188255638 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9729 -0.7425  0.0353  0.8456  3.4780 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95794    0.08524 116.824  < 2e-16 ***
## category_code_LT01_2_count   0.44705    0.09535   4.688 3.57e-06 ***
## category_code_LT01_3_count   0.20304    0.11436   1.776   0.0764 .  
## category_code_LT01_4_count   0.56715    0.10037   5.651 2.71e-08 ***
## category_code_LT01_5_count   0.90897    0.06028  15.080  < 2e-16 ***
## category_code_LT01_11_count  0.19978    0.11821   1.690   0.0917 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 492 degrees of freedom
## Multiple R-squared:  0.6457, Adjusted R-squared:  0.6421 
## F-statistic: 179.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 0.64001868128848 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9672 -0.7300  0.0665  0.8724  3.4827 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.950728   0.085379 116.548  < 2e-16 ***
## category_code_LT01_2_count   0.504322   0.090222   5.590 3.77e-08 ***
## category_code_LT01_3_count   0.240222   0.112710   2.131   0.0336 *  
## category_code_LT01_4_count   0.615489   0.096707   6.364 4.49e-10 ***
## category_code_LT01_5_count   0.911255   0.060676  15.018  < 2e-16 ***
## category_code_LT01_12_count -0.002912   0.201848  -0.014   0.9885    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:   0.64 
## F-statistic: 177.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 0.640072235910808 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9669 -0.7366  0.0596  0.8728  3.4832 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95070    0.08537 116.557  < 2e-16 ***
## category_code_LT01_2_count   0.50305    0.08951   5.620 3.20e-08 ***
## category_code_LT01_3_count   0.23986    0.11255   2.131   0.0336 *  
## category_code_LT01_4_count   0.61302    0.09689   6.327 5.63e-10 ***
## category_code_LT01_5_count   0.91079    0.06045  15.067  < 2e-16 ***
## category_code_LT01_13_count  0.06436    0.23754   0.271   0.7865    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6401 
## F-statistic: 177.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 0.640059347287083 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9670 -0.7252  0.0714  0.8729  3.4835 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95162    0.08546 116.452  < 2e-16 ***
## category_code_LT01_2_count   0.50279    0.08960   5.611 3.36e-08 ***
## category_code_LT01_3_count   0.24156    0.11271   2.143   0.0326 *  
## category_code_LT01_4_count   0.61195    0.09759   6.270 7.89e-10 ***
## category_code_LT01_5_count   0.90968    0.06077  14.970  < 2e-16 ***
## category_code_LT01_14_count  0.07565    0.32029   0.236   0.8134    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6401 
## F-statistic: 177.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 0.640054769550945 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9667 -0.7371  0.0723  0.8730  3.4834 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95053    0.08538 116.546  < 2e-16 ***
## category_code_LT01_2_count   0.50489    0.08948   5.642 2.83e-08 ***
## category_code_LT01_3_count   0.24315    0.11336   2.145   0.0324 *  
## category_code_LT01_4_count   0.61626    0.09657   6.381 4.06e-10 ***
## category_code_LT01_5_count   0.91082    0.06046  15.066  < 2e-16 ***
## category_code_LT01_15_count -0.16407    0.73718  -0.223   0.8240    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6401 
## F-statistic: 177.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 0.640035664938674 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9673 -0.7329  0.0687  0.8724  3.4827 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95093    0.08539 116.539  < 2e-16 ***
## category_code_LT01_2_count   0.50287    0.08981   5.599 3.59e-08 ***
## category_code_LT01_3_count   0.23838    0.11313   2.107   0.0356 *  
## category_code_LT01_4_count   0.61641    0.09673   6.373 4.27e-10 ***
## category_code_LT01_5_count   0.91103    0.06044  15.072  < 2e-16 ***
## category_code_LT01_16_count  0.17572    1.14820   0.153   0.8784    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:   0.64 
## F-statistic: 177.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 0.628064261355259 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9877 -0.7488  0.0036  0.8686  3.8406 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96038    0.08684 114.699  < 2e-16 ***
## category_code_LT01_2_count  0.65778    0.08306   7.919  1.6e-14 ***
## category_code_LT01_3_count  0.40586    0.10866   3.735 0.000210 ***
## category_code_LT01_5_count  0.92686    0.06143  15.087  < 2e-16 ***
## category_code_LT01_6_count  0.42841    0.15091   2.839 0.004714 ** 
## category_code_LT01_7_count  0.57839    0.14965   3.865 0.000126 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 492 degrees of freedom
## Multiple R-squared:  0.6318, Adjusted R-squared:  0.6281 
## F-statistic: 168.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 0.616979482096433 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0055 -0.7612  0.0182  0.8756  3.8394 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96151    0.08816 112.992  < 2e-16 ***
## category_code_LT01_2_count  0.74717    0.08091   9.234  < 2e-16 ***
## category_code_LT01_3_count  0.45200    0.10967   4.121 4.42e-05 ***
## category_code_LT01_5_count  0.95093    0.06282  15.138  < 2e-16 ***
## category_code_LT01_6_count  0.44596    0.15323   2.910  0.00377 ** 
## category_code_LT01_8_count -0.14254    0.27615  -0.516  0.60598    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.617 
## F-statistic: 161.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 0.618343945751164 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9943 -0.7654  0.0317  0.8783  3.8433 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95768    0.08798 113.176  < 2e-16 ***
## category_code_LT01_2_count  0.73253    0.08147   8.991  < 2e-16 ***
## category_code_LT01_3_count  0.42742    0.11065   3.863 0.000127 ***
## category_code_LT01_5_count  0.94021    0.06217  15.124  < 2e-16 ***
## category_code_LT01_6_count  0.43424    0.15294   2.839 0.004708 ** 
## category_code_LT01_9_count  0.32582    0.22889   1.423 0.155228    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 492 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6183 
## F-statistic:   162 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 0.616823085229207 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9951 -0.7660 -0.0066  0.8957  3.8468 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95419    0.09121 109.139  < 2e-16 ***
## category_code_LT01_2_count   0.74720    0.08096   9.229  < 2e-16 ***
## category_code_LT01_3_count   0.44595    0.11116   4.012 6.96e-05 ***
## category_code_LT01_5_count   0.94640    0.06216  15.226  < 2e-16 ***
## category_code_LT01_6_count   0.43710    0.15465   2.826   0.0049 ** 
## category_code_LT01_10_count  0.02965    0.11585   0.256   0.7981    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.6168 
## F-statistic:   161 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 0.623519121313562 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0065 -0.7745  0.0494  0.8412  3.8293 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97163    0.08745 114.023  < 2e-16 ***
## category_code_LT01_2_count   0.61565    0.09174   6.711 5.34e-11 ***
## category_code_LT01_3_count   0.35745    0.11313   3.160  0.00168 ** 
## category_code_LT01_5_count   0.93773    0.06167  15.206  < 2e-16 ***
## category_code_LT01_6_count   0.37800    0.15333   2.465  0.01403 *  
## category_code_LT01_11_count  0.34868    0.11743   2.969  0.00313 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 492 degrees of freedom
## Multiple R-squared:  0.6273, Adjusted R-squared:  0.6235 
## F-statistic: 165.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 0.616777780454032 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0006 -0.7616  0.0226  0.8868  3.8408 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96018    0.08815 112.995  < 2e-16 ***
## category_code_LT01_2_count   0.74678    0.08193   9.115  < 2e-16 ***
## category_code_LT01_3_count   0.44998    0.10991   4.094 4.95e-05 ***
## category_code_LT01_5_count   0.94571    0.06238  15.160  < 2e-16 ***
## category_code_LT01_6_count   0.44126    0.15398   2.866  0.00434 ** 
## category_code_LT01_12_count  0.01787    0.20897   0.086  0.93187    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.6168 
## F-statistic:   161 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 0.617318679058539 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9991 -0.7554  0.0144  0.8969  3.8412 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95979    0.08809 113.069  < 2e-16 ***
## category_code_LT01_2_count   0.74021    0.08138   9.096  < 2e-16 ***
## category_code_LT01_3_count   0.44653    0.10970   4.071 5.46e-05 ***
## category_code_LT01_5_count   0.94420    0.06215  15.192  < 2e-16 ***
## category_code_LT01_6_count   0.44339    0.15303   2.897  0.00393 ** 
## category_code_LT01_13_count  0.20449    0.24393   0.838  0.40227    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6173 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 0.618210941554467 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9969 -0.7638 -0.0193  0.8995  3.8368 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96417    0.08803 113.190  < 2e-16 ***
## category_code_LT01_2_count   0.72620    0.08233   8.821  < 2e-16 ***
## category_code_LT01_3_count   0.44922    0.10947   4.104 4.76e-05 ***
## category_code_LT01_5_count   0.93471    0.06260  14.931  < 2e-16 ***
## category_code_LT01_6_count   0.45743    0.15323   2.985  0.00297 ** 
## category_code_LT01_14_count  0.44524    0.32698   1.362  0.17392    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6182 
## F-statistic:   162 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 0.61677713905832 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0007 -0.7635  0.0223  0.8872  3.8408 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96011    0.08815 112.988  < 2e-16 ***
## category_code_LT01_2_count   0.74823    0.08104   9.232  < 2e-16 ***
## category_code_LT01_3_count   0.45181    0.11070   4.082 5.22e-05 ***
## category_code_LT01_5_count   0.94604    0.06217  15.217  < 2e-16 ***
## category_code_LT01_6_count   0.44312    0.15325   2.891    0.004 ** 
## category_code_LT01_15_count -0.06129    0.76061  -0.081    0.936    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.6168 
## F-statistic:   161 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 0.616773615206092 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0009 -0.7631  0.0221  0.8880  3.8407 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96023    0.08815 112.986  < 2e-16 ***
## category_code_LT01_2_count   0.74751    0.08135   9.189  < 2e-16 ***
## category_code_LT01_3_count   0.45013    0.11019   4.085 5.14e-05 ***
## category_code_LT01_5_count   0.94611    0.06216  15.220  < 2e-16 ***
## category_code_LT01_6_count   0.44340    0.15407   2.878  0.00418 ** 
## category_code_LT01_16_count  0.05276    1.18918   0.044  0.96463    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.6168 
## F-statistic:   161 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 0.622191165594111 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0214 -0.7363 -0.0012  0.8301  3.8252 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97574    0.08743 114.104  < 2e-16 ***
## category_code_LT01_2_count  0.73782    0.07868   9.377  < 2e-16 ***
## category_code_LT01_3_count  0.44788    0.10860   4.124 4.37e-05 ***
## category_code_LT01_5_count  0.95333    0.06214  15.341  < 2e-16 ***
## category_code_LT01_7_count  0.59159    0.15088   3.921 0.000101 ***
## category_code_LT01_8_count -0.14659    0.27420  -0.535 0.593155    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 492 degrees of freedom
## Multiple R-squared:  0.626,  Adjusted R-squared:  0.6222 
## F-statistic: 164.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 0.623030902740002 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0110 -0.7581 -0.0131  0.8331  3.8290 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97198    0.08731 114.217  < 2e-16 ***
## category_code_LT01_2_count  0.72710    0.07917   9.184  < 2e-16 ***
## category_code_LT01_3_count  0.42793    0.10957   3.906 0.000107 ***
## category_code_LT01_5_count  0.94369    0.06150  15.343  < 2e-16 ***
## category_code_LT01_7_count  0.57176    0.15131   3.779 0.000177 ***
## category_code_LT01_9_count  0.26849    0.22835   1.176 0.240256    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 492 degrees of freedom
## Multiple R-squared:  0.6268, Adjusted R-squared:  0.623 
## F-statistic: 165.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 0.62208647579957 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0073 -0.7457 -0.0272  0.8379  3.8359 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96507    0.09058 110.017  < 2e-16 ***
## category_code_LT01_2_count   0.73643    0.07884   9.341  < 2e-16 ***
## category_code_LT01_3_count   0.43895    0.11025   3.981 7.89e-05 ***
## category_code_LT01_5_count   0.94843    0.06145  15.433  < 2e-16 ***
## category_code_LT01_7_count   0.58460    0.15119   3.867 0.000125 ***
## category_code_LT01_10_count  0.04415    0.11421   0.387 0.699234    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6259, Adjusted R-squared:  0.6221 
## F-statistic: 164.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 0.62629164858676 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0200 -0.7696  0.0221  0.8169  3.8189 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98201    0.08697 114.778  < 2e-16 ***
## category_code_LT01_2_count   0.63555    0.08933   7.114 3.99e-12 ***
## category_code_LT01_3_count   0.37261    0.11231   3.318 0.000975 ***
## category_code_LT01_5_count   0.94221    0.06116  15.405  < 2e-16 ***
## category_code_LT01_7_count   0.48730    0.15588   3.126 0.001876 ** 
## category_code_LT01_11_count  0.28708    0.12038   2.385 0.017465 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6263 
## F-statistic: 167.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 0.622065137494593 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0148 -0.7562 -0.0111  0.8302  3.8269 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97407    0.08740 114.120  < 2e-16 ***
## category_code_LT01_2_count   0.73297    0.08019   9.141  < 2e-16 ***
## category_code_LT01_3_count   0.44335    0.10892   4.070 5.47e-05 ***
## category_code_LT01_5_count   0.94625    0.06175  15.324  < 2e-16 ***
## category_code_LT01_7_count   0.58819    0.15082   3.900  0.00011 ***
## category_code_LT01_12_count  0.07199    0.20639   0.349  0.72739    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6259, Adjusted R-squared:  0.6221 
## F-statistic: 164.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 0.622049250661738 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0160 -0.7607 -0.0148  0.8385  3.8268 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97413    0.08740 114.120  < 2e-16 ***
## category_code_LT01_2_count   0.73651    0.07890   9.334  < 2e-16 ***
## category_code_LT01_3_count   0.44533    0.10863   4.099 4.85e-05 ***
## category_code_LT01_5_count   0.94784    0.06148  15.418  < 2e-16 ***
## category_code_LT01_7_count   0.58242    0.15212   3.829 0.000146 ***
## category_code_LT01_13_count  0.07770    0.24453   0.318 0.750802    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6259, Adjusted R-squared:  0.622 
## F-statistic: 164.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 0.622443639088728 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0151 -0.7468 -0.0016  0.8221  3.8241 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97684    0.08742 114.131  < 2e-16 ***
## category_code_LT01_2_count   0.72939    0.07947   9.178  < 2e-16 ***
## category_code_LT01_3_count   0.44729    0.10854   4.121 4.42e-05 ***
## category_code_LT01_5_count   0.94261    0.06186  15.238  < 2e-16 ***
## category_code_LT01_7_count   0.57723    0.15145   3.811 0.000156 ***
## category_code_LT01_14_count  0.25556    0.32588   0.784 0.433285    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 492 degrees of freedom
## Multiple R-squared:  0.6262, Adjusted R-squared:  0.6224 
## F-statistic: 164.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 0.62198674362359 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0167 -0.7559 -0.0170  0.8282  3.8266 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97437    0.08741 114.110  < 2e-16 ***
## category_code_LT01_2_count   0.73748    0.07894   9.342  < 2e-16 ***
## category_code_LT01_3_count   0.44412    0.10975   4.047 6.03e-05 ***
## category_code_LT01_5_count   0.94851    0.06147  15.430  < 2e-16 ***
## category_code_LT01_7_count   0.58934    0.15088   3.906 0.000107 ***
## category_code_LT01_15_count  0.10572    0.75513   0.140 0.888720    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6258, Adjusted R-squared:  0.622 
## F-statistic: 164.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 0.621989787540263 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0163 -0.7584 -0.0177  0.8368  3.8269 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97402    0.08742 114.091  < 2e-16 ***
## category_code_LT01_2_count   0.73923    0.07890   9.369  < 2e-16 ***
## category_code_LT01_3_count   0.44777    0.10899   4.108 4.67e-05 ***
## category_code_LT01_5_count   0.94843    0.06146  15.431  < 2e-16 ***
## category_code_LT01_7_count   0.58803    0.15090   3.897 0.000111 ***
## category_code_LT01_16_count -0.18028    1.17446  -0.153 0.878070    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6258, Adjusted R-squared:  0.622 
## F-statistic: 164.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 0.61224404354735 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0273 -0.7623  0.0255  0.8764  3.8282 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97275    0.08859 112.572  < 2e-16 ***
## category_code_LT01_2_count  0.81434    0.07678  10.606  < 2e-16 ***
## category_code_LT01_3_count  0.46868    0.11065   4.235 2.72e-05 ***
## category_code_LT01_5_count  0.96605    0.06290  15.358  < 2e-16 ***
## category_code_LT01_8_count -0.12271    0.27776  -0.442    0.659    
## category_code_LT01_9_count  0.35424    0.23066   1.536    0.125    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 492 degrees of freedom
## Multiple R-squared:  0.6161, Adjusted R-squared:  0.6122 
## F-statistic: 157.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 0.610731135982143 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0187 -0.7557  0.0206  0.8354  3.8412 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95973    0.09194 108.325  < 2e-16 ***
## category_code_LT01_2_count   0.82831    0.07629  10.858  < 2e-16 ***
## category_code_LT01_3_count   0.48126    0.11141   4.320 1.89e-05 ***
## category_code_LT01_5_count   0.97252    0.06288  15.465  < 2e-16 ***
## category_code_LT01_8_count  -0.11254    0.27821  -0.405    0.686    
## category_code_LT01_10_count  0.07647    0.11564   0.661    0.509    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6146, Adjusted R-squared:  0.6107 
## F-statistic:   157 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 0.618953664839687 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0354 -0.7683 -0.0070  0.8221  4.0601 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98588    0.08785 113.664  < 2e-16 ***
## category_code_LT01_2_count   0.67143    0.08947   7.504 2.92e-13 ***
## category_code_LT01_3_count   0.38349    0.11344   3.381 0.000781 ***
## category_code_LT01_5_count   0.95881    0.06235  15.377  < 2e-16 ***
## category_code_LT01_8_count  -0.09115    0.27525  -0.331 0.740673    
## category_code_LT01_11_count  0.38903    0.11696   3.326 0.000946 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 492 degrees of freedom
## Multiple R-squared:  0.6228, Adjusted R-squared:  0.619 
## F-statistic: 162.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 0.610512004973453 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0328 -0.7650  0.0030  0.8604  3.8255 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97545    0.08877 112.376  < 2e-16 ***
## category_code_LT01_2_count   0.82641    0.07766  10.641  < 2e-16 ***
## category_code_LT01_3_count   0.49110    0.10995   4.467 9.87e-06 ***
## category_code_LT01_5_count   0.97018    0.06317  15.358  < 2e-16 ***
## category_code_LT01_8_count  -0.11301    0.27843  -0.406    0.685    
## category_code_LT01_12_count  0.08392    0.20966   0.400    0.689    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6105 
## F-statistic: 156.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 0.610883712841485 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0325 -0.7748  0.0083  0.8839  3.8258 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97515    0.08873 112.425  < 2e-16 ***
## category_code_LT01_2_count   0.82560    0.07651  10.791  < 2e-16 ***
## category_code_LT01_3_count   0.49062    0.10967   4.474 9.56e-06 ***
## category_code_LT01_5_count   0.97023    0.06294  15.416  < 2e-16 ***
## category_code_LT01_8_count  -0.09639    0.27854  -0.346    0.729    
## category_code_LT01_13_count  0.19560    0.24636   0.794    0.428    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6148, Adjusted R-squared:  0.6109 
## F-statistic: 157.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 0.61143004418557 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0323 -0.7690  0.0203  0.8475  3.8215 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97949    0.08873 112.475  < 2e-16 ***
## category_code_LT01_2_count   0.81677    0.07719  10.582  < 2e-16 ***
## category_code_LT01_3_count   0.49470    0.10948   4.519  7.8e-06 ***
## category_code_LT01_5_count   0.96362    0.06330  15.223  < 2e-16 ***
## category_code_LT01_8_count  -0.11464    0.27795  -0.412    0.680    
## category_code_LT01_14_count  0.37853    0.32909   1.150    0.251    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6114 
## F-statistic: 157.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 0.610386165138479 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0347 -0.7652  0.0082  0.8628  3.8253 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97566    0.08879 112.357  < 2e-16 ***
## category_code_LT01_2_count   0.83259    0.07623  10.922  < 2e-16 ***
## category_code_LT01_3_count   0.49403    0.11074   4.461 1.01e-05 ***
## category_code_LT01_5_count   0.97256    0.06293  15.455  < 2e-16 ***
## category_code_LT01_8_count  -0.10890    0.27829  -0.391    0.696    
## category_code_LT01_15_count  0.02724    0.76638   0.036    0.972    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6104 
## F-statistic: 156.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 0.610436032533492 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0341 -0.7647  0.0042  0.8583  3.8258 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97518    0.08879 112.340  < 2e-16 ***
## category_code_LT01_2_count   0.83407    0.07618  10.948  < 2e-16 ***
## category_code_LT01_3_count   0.49685    0.10998   4.518 7.83e-06 ***
## category_code_LT01_5_count   0.97248    0.06291  15.459  < 2e-16 ***
## category_code_LT01_8_count  -0.10542    0.27858  -0.378    0.705    
## category_code_LT01_16_count -0.30239    1.19305  -0.253    0.800    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6104 
## F-statistic: 156.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 0.612293718618744 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0111 -0.7489  0.0347  0.8733  3.8416 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95937    0.09173 108.573  < 2e-16 ***
## category_code_LT01_2_count   0.81173    0.07698  10.544  < 2e-16 ***
## category_code_LT01_3_count   0.45798    0.11217   4.083 5.19e-05 ***
## category_code_LT01_5_count   0.96201    0.06218  15.471  < 2e-16 ***
## category_code_LT01_9_count   0.33942    0.23163   1.465    0.143    
## category_code_LT01_10_count  0.05892    0.11594   0.508    0.612    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 492 degrees of freedom
## Multiple R-squared:  0.6162, Adjusted R-squared:  0.6123 
## F-statistic:   158 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 0.620418742187549 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0251 -0.7716  0.0186  0.8138  4.1200 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98207    0.08767 113.862  < 2e-16 ***
## category_code_LT01_2_count   0.65683    0.08987   7.309  1.1e-12 ***
## category_code_LT01_3_count   0.36009    0.11422   3.153  0.00172 ** 
## category_code_LT01_5_count   0.94950    0.06164  15.403  < 2e-16 ***
## category_code_LT01_9_count   0.32352    0.22825   1.417  0.15699    
## category_code_LT01_11_count  0.38373    0.11679   3.286  0.00109 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 492 degrees of freedom
## Multiple R-squared:  0.6242, Adjusted R-squared:  0.6204 
## F-statistic: 163.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 0.612208759821449 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0213 -0.7609  0.0300  0.8796  3.8296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97133    0.08855 112.602  < 2e-16 ***
## category_code_LT01_2_count   0.80841    0.07842  10.309  < 2e-16 ***
## category_code_LT01_3_count   0.46402    0.11098   4.181 3.43e-05 ***
## category_code_LT01_5_count   0.95948    0.06250  15.353  < 2e-16 ***
## category_code_LT01_9_count   0.35102    0.23055   1.523    0.129    
## category_code_LT01_12_count  0.08108    0.20906   0.388    0.698    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 492 degrees of freedom
## Multiple R-squared:  0.6161, Adjusted R-squared:  0.6122 
## F-statistic: 157.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 0.612747579183146 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0210 -0.7606  0.0230  0.9006  3.8299 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97102    0.08849 112.677  < 2e-16 ***
## category_code_LT01_2_count   0.80562    0.07736  10.414  < 2e-16 ***
## category_code_LT01_3_count   0.46208    0.11070   4.174 3.54e-05 ***
## category_code_LT01_5_count   0.95950    0.06220  15.426  < 2e-16 ***
## category_code_LT01_9_count   0.36414    0.23084   1.577    0.115    
## category_code_LT01_13_count  0.22469    0.24587   0.914    0.361    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 492 degrees of freedom
## Multiple R-squared:  0.6166, Adjusted R-squared:  0.6127 
## F-statistic: 158.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 0.612932143342268 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0213 -0.7647  0.0222  0.8692  3.8258 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97512    0.08854 112.667  < 2e-16 ***
## category_code_LT01_2_count   0.80109    0.07781  10.295  < 2e-16 ***
## category_code_LT01_3_count   0.46879    0.11053   4.241 2.66e-05 ***
## category_code_LT01_5_count   0.95404    0.06259  15.242  < 2e-16 ***
## category_code_LT01_9_count   0.33312    0.23097   1.442    0.150    
## category_code_LT01_14_count  0.34067    0.32931   1.034    0.301    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6168, Adjusted R-squared:  0.6129 
## F-statistic: 158.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 0.612096910908694 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0233 -0.7712  0.0229  0.8858  3.8293 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97161    0.08857 112.588  < 2e-16 ***
## category_code_LT01_2_count   0.81402    0.07704  10.567  < 2e-16 ***
## category_code_LT01_3_count   0.46593    0.11185   4.166 3.67e-05 ***
## category_code_LT01_5_count   0.96198    0.06221  15.464  < 2e-16 ***
## category_code_LT01_9_count   0.35176    0.23076   1.524    0.128    
## category_code_LT01_15_count  0.07055    0.76526   0.092    0.927    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 492 degrees of freedom
## Multiple R-squared:  0.616,  Adjusted R-squared:  0.6121 
## F-statistic: 157.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 0.61215909829714 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0227 -0.7641  0.0219  0.8765  3.8299 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97105    0.08857 112.574  < 2e-16 ***
## category_code_LT01_2_count   0.81601    0.07694  10.605  < 2e-16 ***
## category_code_LT01_3_count   0.47004    0.11098   4.235 2.72e-05 ***
## category_code_LT01_5_count   0.96196    0.06219  15.467  < 2e-16 ***
## category_code_LT01_9_count   0.35195    0.23059   1.526    0.128    
## category_code_LT01_16_count -0.35154    1.18919  -0.296    0.768    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 492 degrees of freedom
## Multiple R-squared:  0.6161, Adjusted R-squared:  0.6122 
## F-statistic: 157.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 0.61919986187474 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0166 -0.7590  0.0025  0.8366  4.1019 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96939    0.09096 109.597  < 2e-16 ***
## category_code_LT01_2_count   0.66684    0.08969   7.435 4.67e-13 ***
## category_code_LT01_3_count   0.36914    0.11507   3.208 0.001424 ** 
## category_code_LT01_5_count   0.95552    0.06159  15.514  < 2e-16 ***
## category_code_LT01_10_count  0.07480    0.11435   0.654 0.513366    
## category_code_LT01_11_count  0.38963    0.11690   3.333 0.000924 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 492 degrees of freedom
## Multiple R-squared:  0.623,  Adjusted R-squared:  0.6192 
## F-statistic: 162.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 0.610708076048813 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0136 -0.7495  0.0082  0.8491  3.8421 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95885    0.09192 108.347  < 2e-16 ***
## category_code_LT01_2_count   0.82265    0.07790  10.561  < 2e-16 ***
## category_code_LT01_3_count   0.47704    0.11168   4.271 2.33e-05 ***
## category_code_LT01_5_count   0.96637    0.06245  15.474  < 2e-16 ***
## category_code_LT01_10_count  0.07430    0.11567   0.642    0.521    
## category_code_LT01_12_count  0.07685    0.20955   0.367    0.714    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6146, Adjusted R-squared:  0.6107 
## F-statistic: 156.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 0.611105064064972 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0139 -0.7506  0.0165  0.8517  3.8420 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95894    0.09187 108.403  < 2e-16 ***
## category_code_LT01_2_count   0.82134    0.07677  10.699  < 2e-16 ***
## category_code_LT01_3_count   0.47666    0.11140   4.279 2.26e-05 ***
## category_code_LT01_5_count   0.96678    0.06216  15.554  < 2e-16 ***
## category_code_LT01_10_count  0.07310    0.11560   0.632    0.527    
## category_code_LT01_13_count  0.19631    0.24599   0.798    0.425    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.615,  Adjusted R-squared:  0.6111 
## F-statistic: 157.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 0.611428732725759 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0184 -0.7574  0.0164  0.8574  3.8331 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96787    0.09226 108.043  < 2e-16 ***
## category_code_LT01_2_count   0.81539    0.07728  10.552  < 2e-16 ***
## category_code_LT01_3_count   0.48481    0.11137   4.353 1.63e-05 ***
## category_code_LT01_5_count   0.96038    0.06261  15.339  < 2e-16 ***
## category_code_LT01_10_count  0.04862    0.11847   0.410    0.682    
## category_code_LT01_14_count  0.34532    0.33745   1.023    0.307    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6114 
## F-statistic: 157.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 0.610601700023214 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0151 -0.7522  0.0109  0.8401  3.8422 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.958785   0.091955 108.300  < 2e-16 ***
## category_code_LT01_2_count   0.828459   0.076479  10.833  < 2e-16 ***
## category_code_LT01_3_count   0.480169   0.112343   4.274  2.3e-05 ***
## category_code_LT01_5_count   0.968624   0.062167  15.581  < 2e-16 ***
## category_code_LT01_10_count  0.075565   0.115839   0.652    0.514    
## category_code_LT01_15_count -0.005179   0.767466  -0.007    0.995    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6106 
## F-statistic: 156.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 0.61066631120853 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0145 -0.7477  0.0102  0.8392  3.8428 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95818    0.09195 108.303  < 2e-16 ***
## category_code_LT01_2_count   0.82982    0.07645  10.854  < 2e-16 ***
## category_code_LT01_3_count   0.48254    0.11172   4.319 1.89e-05 ***
## category_code_LT01_5_count   0.96873    0.06215  15.587  < 2e-16 ***
## category_code_LT01_10_count  0.07622    0.11565   0.659    0.510    
## category_code_LT01_16_count -0.34059    1.19160  -0.286    0.775    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6146, Adjusted R-squared:  0.6107 
## F-statistic: 156.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 0.619005387850976 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0344 -0.7696 -0.0129  0.8170  4.0583 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98555    0.08782 113.709  < 2e-16 ***
## category_code_LT01_2_count   0.67296    0.08957   7.513 2.74e-13 ***
## category_code_LT01_3_count   0.38251    0.11336   3.374 0.000799 ***
## category_code_LT01_5_count   0.95787    0.06184  15.491  < 2e-16 ***
## category_code_LT01_11_count  0.40188    0.12043   3.337 0.000911 ***
## category_code_LT01_12_count -0.08965    0.21341  -0.420 0.674611    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 492 degrees of freedom
## Multiple R-squared:  0.6228, Adjusted R-squared:  0.619 
## F-statistic: 162.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 0.619148908234704 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0310 -0.7742  0.0047  0.8332  4.0722 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98459    0.08779 113.729  < 2e-16 ***
## category_code_LT01_2_count   0.66772    0.08963   7.450 4.23e-13 ***
## category_code_LT01_3_count   0.38066    0.11337   3.358 0.000847 ***
## category_code_LT01_5_count   0.95440    0.06163  15.487  < 2e-16 ***
## category_code_LT01_11_count  0.38506    0.11717   3.286 0.001088 ** 
## category_code_LT01_13_count  0.14673    0.24389   0.602 0.547708    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 492 degrees of freedom
## Multiple R-squared:  0.623,  Adjusted R-squared:  0.6191 
## F-statistic: 162.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 0.619580672560501 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0302 -0.7743  0.0119  0.8225  4.0797 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98795    0.08779 113.765  < 2e-16 ***
## category_code_LT01_2_count   0.66067    0.09006   7.336 9.16e-13 ***
## category_code_LT01_3_count   0.38411    0.11329   3.390 0.000754 ***
## category_code_LT01_5_count   0.94833    0.06203  15.289  < 2e-16 ***
## category_code_LT01_11_count  0.38314    0.11705   3.273 0.001137 ** 
## category_code_LT01_14_count  0.31295    0.32614   0.960 0.337748    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6234, Adjusted R-squared:  0.6196 
## F-statistic: 162.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 0.618873007359811 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0321 -0.7738 -0.0028  0.8257  4.0612 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98494    0.08782 113.692  < 2e-16 ***
## category_code_LT01_2_count   0.67146    0.08957   7.496 3.08e-13 ***
## category_code_LT01_3_count   0.38326    0.11431   3.353 0.000861 ***
## category_code_LT01_5_count   0.95553    0.06163  15.504  < 2e-16 ***
## category_code_LT01_11_count  0.39005    0.11701   3.334 0.000922 ***
## category_code_LT01_15_count -0.05631    0.75834  -0.074 0.940833    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 492 degrees of freedom
## Multiple R-squared:  0.6227, Adjusted R-squared:  0.6189 
## F-statistic: 162.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 0.618881027132609 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0321 -0.7735 -0.0099  0.8242  4.0599 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98476    0.08784 113.671  < 2e-16 ***
## category_code_LT01_2_count   0.67206    0.08976   7.487 3.28e-13 ***
## category_code_LT01_3_count   0.38350    0.11386   3.368 0.000816 ***
## category_code_LT01_5_count   0.95569    0.06162  15.510  < 2e-16 ***
## category_code_LT01_11_count  0.38912    0.11707   3.324 0.000954 ***
## category_code_LT01_16_count -0.14863    1.17988  -0.126 0.899809    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 492 degrees of freedom
## Multiple R-squared:  0.6227, Adjusted R-squared:  0.6189 
## F-statistic: 162.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 0.610893108963177 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0275 -0.7635  0.0056  0.8862  3.8270 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97397    0.08868 112.468  < 2e-16 ***
## category_code_LT01_2_count   0.81978    0.07810  10.497  < 2e-16 ***
## category_code_LT01_3_count   0.48621    0.10995   4.422  1.2e-05 ***
## category_code_LT01_5_count   0.96464    0.06247  15.441  < 2e-16 ***
## category_code_LT01_12_count  0.07601    0.20949   0.363    0.717    
## category_code_LT01_13_count  0.19789    0.24607   0.804    0.422    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6148, Adjusted R-squared:  0.6109 
## F-statistic: 157.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 0.611364165162538 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0270 -0.7676  0.0110  0.8425  3.8229 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97807    0.08869 112.503  < 2e-16 ***
## category_code_LT01_2_count   0.81256    0.07861  10.337  < 2e-16 ***
## category_code_LT01_3_count   0.49071    0.10979   4.470 9.74e-06 ***
## category_code_LT01_5_count   0.95808    0.06284  15.246  < 2e-16 ***
## category_code_LT01_12_count  0.06182    0.20997   0.294    0.769    
## category_code_LT01_14_count  0.36821    0.33014   1.115    0.265    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6114 
## F-statistic: 157.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 0.610382995221494 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0291 -0.7639 -0.0053  0.8711  3.8266 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97435    0.08874 112.396  < 2e-16 ***
## category_code_LT01_2_count   0.82645    0.07791  10.608  < 2e-16 ***
## category_code_LT01_3_count   0.48920    0.11108   4.404 1.31e-05 ***
## category_code_LT01_5_count   0.96641    0.06249  15.466  < 2e-16 ***
## category_code_LT01_12_count  0.08095    0.20962   0.386    0.700    
## category_code_LT01_15_count  0.03229    0.76662   0.042    0.966    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6104 
## F-statistic: 156.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 0.610435884038503 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0287 -0.7635 -0.0075  0.8678  3.8271 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97389    0.08875 112.383   <2e-16 ***
## category_code_LT01_2_count   0.82813    0.07786  10.636   <2e-16 ***
## category_code_LT01_3_count   0.49231    0.11031   4.463    1e-05 ***
## category_code_LT01_5_count   0.96650    0.06248  15.470   <2e-16 ***
## category_code_LT01_12_count  0.07927    0.20961   0.378    0.705    
## category_code_LT01_16_count -0.31216    1.19210  -0.262    0.794    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6104 
## F-statistic: 156.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 0.611805626953254 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0268 -0.7675  0.0133  0.8782  3.8230 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97792    0.08864 112.568  < 2e-16 ***
## category_code_LT01_2_count   0.80978    0.07766  10.427  < 2e-16 ***
## category_code_LT01_3_count   0.48946    0.10948   4.471 9.68e-06 ***
## category_code_LT01_5_count   0.95791    0.06260  15.302  < 2e-16 ***
## category_code_LT01_13_count  0.19752    0.24569   0.804    0.422    
## category_code_LT01_14_count  0.37333    0.32890   1.135    0.257    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 492 degrees of freedom
## Multiple R-squared:  0.6157, Adjusted R-squared:  0.6118 
## F-statistic: 157.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 0.61079448712629 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0294 -0.7698  0.0090  0.8928  3.8267 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97423    0.08870 112.455  < 2e-16 ***
## category_code_LT01_2_count   0.82496    0.07677  10.746  < 2e-16 ***
## category_code_LT01_3_count   0.48803    0.11079   4.405  1.3e-05 ***
## category_code_LT01_5_count   0.96695    0.06219  15.548  < 2e-16 ***
## category_code_LT01_13_count  0.20168    0.24649   0.818    0.414    
## category_code_LT01_15_count  0.06389    0.76746   0.083    0.934    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6147, Adjusted R-squared:  0.6108 
## F-statistic:   157 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 0.610832502669635 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0289 -0.7633  0.0028  0.8870  3.8272 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97379    0.08870 112.440  < 2e-16 ***
## category_code_LT01_2_count   0.82675    0.07671  10.778  < 2e-16 ***
## category_code_LT01_3_count   0.49154    0.11001   4.468 9.79e-06 ***
## category_code_LT01_5_count   0.96696    0.06218  15.551  < 2e-16 ***
## category_code_LT01_13_count  0.19771    0.24625   0.803    0.422    
## category_code_LT01_16_count -0.27961    1.19236  -0.235    0.815    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6147, Adjusted R-squared:  0.6108 
## F-statistic:   157 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 0.611295749040611 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0284 -0.7679  0.0159  0.8544  3.8226 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.978318   0.088698 112.497  < 2e-16 ***
## category_code_LT01_2_count  0.816888   0.077381  10.557  < 2e-16 ***
## category_code_LT01_3_count  0.493185   0.110568   4.460 1.01e-05 ***
## category_code_LT01_5_count  0.959724   0.062616  15.327  < 2e-16 ***
## category_code_LT01_14_count 0.375992   0.329162   1.142    0.254    
## category_code_LT01_15_count 0.006521   0.765605   0.009    0.993    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6152, Adjusted R-squared:  0.6113 
## F-statistic: 157.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 0.611328838597944 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0281 -0.7675  0.0152  0.8497  3.8230 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97793    0.08871 112.476  < 2e-16 ***
## category_code_LT01_2_count   0.81813    0.07742  10.568  < 2e-16 ***
## category_code_LT01_3_count   0.49518    0.10981   4.509 8.14e-06 ***
## category_code_LT01_5_count   0.95988    0.06260  15.333  < 2e-16 ***
## category_code_LT01_14_count  0.37205    0.32966   1.129    0.260    
## category_code_LT01_16_count -0.24425    1.19242  -0.205    0.838    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6152, Adjusted R-squared:  0.6113 
## F-statistic: 157.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 0.610322893703739 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0305 -0.7637  0.0076  0.8661  3.8269 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97410    0.08876 112.366  < 2e-16 ***
## category_code_LT01_2_count   0.83410    0.07642  10.915  < 2e-16 ***
## category_code_LT01_3_count   0.49545    0.11115   4.458 1.03e-05 ***
## category_code_LT01_5_count   0.96886    0.06219  15.579  < 2e-16 ***
## category_code_LT01_15_count  0.01389    0.76738   0.018    0.986    
## category_code_LT01_16_count -0.32290    1.19338  -0.271    0.787    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6103 
## F-statistic: 156.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 0.644995652619049 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9594 -0.7162  0.0178  0.8651  3.4954 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95127    0.08482 117.316  < 2e-16 ***
## category_code_LT01_2_count  0.47086    0.08980   5.244 2.34e-07 ***
## category_code_LT01_4_count  0.58453    0.09472   6.171 1.42e-09 ***
## category_code_LT01_5_count  0.89922    0.06026  14.921  < 2e-16 ***
## category_code_LT01_6_count  0.31380    0.14932   2.102  0.03610 *  
## category_code_LT01_7_count  0.40472    0.15021   2.694  0.00729 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 492 degrees of freedom
## Multiple R-squared:  0.6486, Adjusted R-squared:  0.645 
## F-statistic: 181.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 0.639967528513823 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9685 -0.7404  0.0910  0.8935  3.4808 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95085    0.08546 116.441  < 2e-16 ***
## category_code_LT01_2_count  0.50451    0.08952   5.635 2.94e-08 ***
## category_code_LT01_4_count  0.64951    0.09233   7.035 6.73e-12 ***
## category_code_LT01_5_count  0.91285    0.06126  14.901  < 2e-16 ***
## category_code_LT01_6_count  0.31127    0.15049   2.068   0.0391 *  
## category_code_LT01_8_count -0.14354    0.26769  -0.536   0.5921    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:   0.64 
## F-statistic: 177.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 0.641483726549553 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9560 -0.7428  0.0880  0.9226  3.4980 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94634    0.08527 116.652  < 2e-16 ***
## category_code_LT01_2_count  0.48752    0.09006   5.413 9.68e-08 ***
## category_code_LT01_4_count  0.63777    0.09240   6.902 1.58e-11 ***
## category_code_LT01_5_count  0.90136    0.06063  14.867  < 2e-16 ***
## category_code_LT01_6_count  0.29836    0.15017   1.987   0.0475 *  
## category_code_LT01_9_count  0.33877    0.22008   1.539   0.1244    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 492 degrees of freedom
## Multiple R-squared:  0.6451, Adjusted R-squared:  0.6415 
## F-statistic: 178.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 0.640077133528101 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9486 -0.7298  0.0891  0.8875  3.4221 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93427    0.08846 112.308  < 2e-16 ***
## category_code_LT01_2_count   0.50105    0.08972   5.585 3.88e-08 ***
## category_code_LT01_4_count   0.64620    0.09239   6.994 8.74e-12 ***
## category_code_LT01_5_count   0.90811    0.06059  14.987  < 2e-16 ***
## category_code_LT01_6_count   0.29291    0.15204   1.927   0.0546 .  
## category_code_LT01_10_count  0.07332    0.11087   0.661   0.5087    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6401 
## F-statistic: 177.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 0.642263624407467 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9693 -0.7449  0.0519  0.8519  3.4831 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95690    0.08524 116.808  < 2e-16 ***
## category_code_LT01_2_count   0.44012    0.09586   4.591 5.60e-06 ***
## category_code_LT01_4_count   0.58816    0.09764   6.024 3.34e-09 ***
## category_code_LT01_5_count   0.90527    0.06043  14.982  < 2e-16 ***
## category_code_LT01_6_count   0.27737    0.15078   1.840   0.0664 .  
## category_code_LT01_11_count  0.21665    0.11669   1.857   0.0640 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 492 degrees of freedom
## Multiple R-squared:  0.6459, Adjusted R-squared:  0.6423 
## F-statistic: 179.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 0.639765130016582 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9641 -0.7386  0.0848  0.8937  3.4869 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94950    0.08544 116.444  < 2e-16 ***
## category_code_LT01_2_count   0.50635    0.09022   5.613 3.33e-08 ***
## category_code_LT01_4_count   0.64939    0.09256   7.016 7.58e-12 ***
## category_code_LT01_5_count   0.90856    0.06082  14.938  < 2e-16 ***
## category_code_LT01_6_count   0.30948    0.15113   2.048   0.0411 *  
## category_code_LT01_12_count -0.02117    0.20263  -0.105   0.9168    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 492 degrees of freedom
## Multiple R-squared:  0.6434, Adjusted R-squared:  0.6398 
## F-statistic: 177.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 0.639838766570435 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9633 -0.7382  0.0801  0.8854  3.4881 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94942    0.08544 116.454  < 2e-16 ***
## category_code_LT01_2_count   0.50362    0.08965   5.617 3.25e-08 ***
## category_code_LT01_4_count   0.64557    0.09282   6.955 1.13e-11 ***
## category_code_LT01_5_count   0.90750    0.06063  14.967  < 2e-16 ***
## category_code_LT01_6_count   0.30898    0.15042   2.054   0.0405 *  
## category_code_LT01_13_count  0.07936    0.23766   0.334   0.7386    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 492 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6398 
## F-statistic: 177.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 0.639838451272805 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9634 -0.7388  0.0873  0.8919  3.4888 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95067    0.08551 116.370  < 2e-16 ***
## category_code_LT01_2_count   0.50291    0.08979   5.601 3.55e-08 ***
## category_code_LT01_4_count   0.64381    0.09352   6.884 1.78e-11 ***
## category_code_LT01_5_count   0.90578    0.06099  14.852  < 2e-16 ***
## category_code_LT01_6_count   0.31309    0.15118   2.071   0.0389 *  
## category_code_LT01_14_count  0.10719    0.32162   0.333   0.7391    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 492 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6398 
## F-statistic: 177.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 0.639758835924949 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9637 -0.7384  0.0858  0.8948  3.4876 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94946    0.08545 116.439  < 2e-16 ***
## category_code_LT01_2_count   0.50543    0.08968   5.636 2.93e-08 ***
## category_code_LT01_4_count   0.64909    0.09262   7.008 8.01e-12 ***
## category_code_LT01_5_count   0.90798    0.06063  14.975  < 2e-16 ***
## category_code_LT01_6_count   0.30821    0.15052   2.048   0.0411 *  
## category_code_LT01_15_count -0.03533    0.73278  -0.048   0.9616    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 492 degrees of freedom
## Multiple R-squared:  0.6434, Adjusted R-squared:  0.6398 
## F-statistic: 177.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 0.639986643022393 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9633 -0.7394  0.0786  0.9035  3.4884 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94980    0.08542 116.481  < 2e-16 ***
## category_code_LT01_2_count   0.49821    0.09037   5.513 5.71e-08 ***
## category_code_LT01_4_count   0.64951    0.09233   7.035 6.72e-12 ***
## category_code_LT01_5_count   0.90691    0.06063  14.958  < 2e-16 ***
## category_code_LT01_6_count   0.31574    0.15100   2.091    0.037 *  
## category_code_LT01_16_count  0.64254    1.14730   0.560    0.576    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:   0.64 
## F-statistic: 177.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 0.642021399910987 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9830 -0.7136  0.0509  0.8561  3.4644 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96206    0.08511 117.053  < 2e-16 ***
## category_code_LT01_2_count  0.51514    0.08761   5.880 7.58e-09 ***
## category_code_LT01_4_count  0.62604    0.09311   6.723 4.94e-11 ***
## category_code_LT01_5_count  0.91760    0.06086  15.078  < 2e-16 ***
## category_code_LT01_7_count  0.40281    0.15090   2.669  0.00785 ** 
## category_code_LT01_8_count -0.14417    0.26684  -0.540  0.58924    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 492 degrees of freedom
## Multiple R-squared:  0.6456, Adjusted R-squared:  0.642 
## F-statistic: 179.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 0.643206808722967 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9707 -0.7114  0.0338  0.8941  3.4811 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95739    0.08495 117.210  < 2e-16 ***
## category_code_LT01_2_count  0.50000    0.08817   5.671 2.43e-08 ***
## category_code_LT01_4_count  0.61729    0.09313   6.629 8.93e-11 ***
## category_code_LT01_5_count  0.90669    0.06023  15.054  < 2e-16 ***
## category_code_LT01_7_count  0.38081    0.15121   2.518   0.0121 *  
## category_code_LT01_9_count  0.30585    0.22030   1.388   0.1657    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.345 on 492 degrees of freedom
## Multiple R-squared:  0.6468, Adjusted R-squared:  0.6432 
## F-statistic: 180.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 0.642240062291799 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9597 -0.7167  0.0443  0.8658  3.3972 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94251    0.08822 112.704  < 2e-16 ***
## category_code_LT01_2_count   0.50907    0.08798   5.786 1.28e-08 ***
## category_code_LT01_4_count   0.62148    0.09321   6.668 6.99e-11 ***
## category_code_LT01_5_count   0.91220    0.06016  15.163  < 2e-16 ***
## category_code_LT01_7_count   0.39157    0.15118   2.590  0.00988 ** 
## category_code_LT01_10_count  0.08438    0.10959   0.770  0.44171    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 492 degrees of freedom
## Multiple R-squared:  0.6458, Adjusted R-squared:  0.6422 
## F-statistic: 179.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 0.643483529402165 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9817 -0.7141  0.0214  0.8651  3.4686 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96575    0.08496 117.303  < 2e-16 ***
## category_code_LT01_2_count   0.46207    0.09424   4.903 1.28e-06 ***
## category_code_LT01_4_count   0.57972    0.09763   5.938 5.45e-09 ***
## category_code_LT01_5_count   0.91039    0.06007  15.156  < 2e-16 ***
## category_code_LT01_7_count   0.34792    0.15438   2.254   0.0247 *  
## category_code_LT01_11_count  0.18054    0.11877   1.520   0.1291    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.345 on 492 degrees of freedom
## Multiple R-squared:  0.6471, Adjusted R-squared:  0.6435 
## F-statistic: 180.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 0.64181720582343 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9776 -0.7052  0.0646  0.8639  3.4720 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96053    0.08509 117.061  < 2e-16 ***
## category_code_LT01_2_count   0.51419    0.08860   5.804 1.16e-08 ***
## category_code_LT01_4_count   0.62441    0.09348   6.679 6.51e-11 ***
## category_code_LT01_5_count   0.91208    0.06045  15.088  < 2e-16 ***
## category_code_LT01_7_count   0.40016    0.15086   2.653  0.00825 ** 
## category_code_LT01_12_count  0.02135    0.20107   0.106  0.91549    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 492 degrees of freedom
## Multiple R-squared:  0.6454, Adjusted R-squared:  0.6418 
## F-statistic: 179.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 0.641809083437371 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9781 -0.7038  0.0600  0.8610  3.4713 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.960583   0.085088 117.061  < 2e-16 ***
## category_code_LT01_2_count   0.515606   0.087675   5.881 7.54e-09 ***
## category_code_LT01_4_count   0.625340   0.093351   6.699 5.76e-11 ***
## category_code_LT01_5_count   0.912691   0.060202  15.161  < 2e-16 ***
## category_code_LT01_7_count   0.400297   0.151849   2.636  0.00865 ** 
## category_code_LT01_13_count -0.002557   0.238509  -0.011  0.99145    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 492 degrees of freedom
## Multiple R-squared:  0.6454, Adjusted R-squared:  0.6418 
## F-statistic: 179.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 0.641810589010567 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9781 -0.7057  0.0587  0.8588  3.4712 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96040    0.08518 116.936  < 2e-16 ***
## category_code_LT01_2_count   0.51575    0.08771   5.880 7.58e-09 ***
## category_code_LT01_4_count   0.62580    0.09381   6.671 6.85e-11 ***
## category_code_LT01_5_count   0.91295    0.06048  15.096  < 2e-16 ***
## category_code_LT01_7_count   0.40056    0.15117   2.650  0.00831 ** 
## category_code_LT01_14_count -0.01494    0.31969  -0.047  0.96275    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 492 degrees of freedom
## Multiple R-squared:  0.6454, Adjusted R-squared:  0.6418 
## F-statistic: 179.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 0.641820700078447 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9782 -0.7027  0.0547  0.8617  3.4711 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96064    0.08509 117.063  < 2e-16 ***
## category_code_LT01_2_count   0.51479    0.08785   5.860 8.49e-09 ***
## category_code_LT01_4_count   0.62417    0.09354   6.673 6.77e-11 ***
## category_code_LT01_5_count   0.91279    0.06020  15.163  < 2e-16 ***
## category_code_LT01_7_count   0.40078    0.15095   2.655  0.00819 ** 
## category_code_LT01_15_count  0.09261    0.73053   0.127  0.89917    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 492 degrees of freedom
## Multiple R-squared:  0.6454, Adjusted R-squared:  0.6418 
## F-statistic: 179.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 0.64192862433659 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9781 -0.7003  0.0583  0.8607  3.4715 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96097    0.08508 117.078  < 2e-16 ***
## category_code_LT01_2_count   0.51128    0.08825   5.793 1.23e-08 ***
## category_code_LT01_4_count   0.62640    0.09316   6.724 4.91e-11 ***
## category_code_LT01_5_count   0.91209    0.06020  15.151  < 2e-16 ***
## category_code_LT01_7_count   0.40095    0.15085   2.658  0.00812 ** 
## category_code_LT01_16_count  0.46194    1.13940   0.405  0.68534    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 492 degrees of freedom
## Multiple R-squared:  0.6455, Adjusted R-squared:  0.6419 
## F-statistic: 179.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 0.638795768194382 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9778 -0.7548  0.0611  0.8692  3.4693 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95637    0.08551 116.432  < 2e-16 ***
## category_code_LT01_2_count  0.52823    0.08798   6.004 3.74e-09 ***
## category_code_LT01_4_count  0.67616    0.09082   7.445 4.38e-13 ***
## category_code_LT01_5_count  0.91830    0.06121  15.002  < 2e-16 ***
## category_code_LT01_8_count -0.13584    0.26806  -0.507    0.613    
## category_code_LT01_9_count  0.36077    0.22085   1.634    0.103    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.354 on 492 degrees of freedom
## Multiple R-squared:  0.6424, Adjusted R-squared:  0.6388 
## F-statistic: 176.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 0.63752617236991 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9630 -0.7482  0.0592  0.8483  3.3645 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93719    0.08879 111.918  < 2e-16 ***
## category_code_LT01_2_count   0.53941    0.08776   6.147 1.64e-09 ***
## category_code_LT01_4_count   0.68259    0.09088   7.511 2.79e-13 ***
## category_code_LT01_5_count   0.92470    0.06117  15.116  < 2e-16 ***
## category_code_LT01_8_count  -0.12674    0.26844  -0.472    0.637    
## category_code_LT01_10_count  0.10645    0.11004   0.967    0.334    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 492 degrees of freedom
## Multiple R-squared:  0.6412, Adjusted R-squared:  0.6375 
## F-statistic: 175.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 0.639926304185589 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9898 -0.7513  0.0797  0.8509  3.4564 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96695    0.08542 116.680  < 2e-16 ***
## category_code_LT01_2_count   0.47194    0.09461   4.988 8.47e-07 ***
## category_code_LT01_4_count   0.61775    0.09677   6.384 4.00e-10 ***
## category_code_LT01_5_count   0.92045    0.06101  15.086  < 2e-16 ***
## category_code_LT01_8_count  -0.10982    0.26752  -0.411   0.6816    
## category_code_LT01_11_count  0.23914    0.11639   2.055   0.0404 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6399 
## F-statistic: 177.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 0.636846392392106 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9857 -0.7494  0.0513  0.8370  3.4588 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95983    0.08572 116.194  < 2e-16 ***
## category_code_LT01_2_count   0.54701    0.08832   6.194 1.24e-09 ***
## category_code_LT01_4_count   0.68809    0.09108   7.555 2.06e-13 ***
## category_code_LT01_5_count   0.92471    0.06145  15.047  < 2e-16 ***
## category_code_LT01_8_count  -0.12173    0.26881  -0.453    0.651    
## category_code_LT01_12_count  0.02318    0.20260   0.114    0.909    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 492 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6368 
## F-statistic: 175.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 0.636888134796744 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9857 -0.7494  0.0410  0.8447  3.4588 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95980    0.08571 116.201  < 2e-16 ***
## category_code_LT01_2_count   0.54739    0.08743   6.261 8.35e-10 ***
## category_code_LT01_4_count   0.68657    0.09119   7.529 2.46e-13 ***
## category_code_LT01_5_count   0.92478    0.06126  15.097  < 2e-16 ***
## category_code_LT01_8_count  -0.11647    0.26904  -0.433    0.665    
## category_code_LT01_13_count  0.06307    0.23898   0.264    0.792    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 492 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6369 
## F-statistic: 175.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 0.636848779709132 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9861 -0.7500  0.0502  0.8351  3.4584 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96039    0.08581 116.074  < 2e-16 ***
## category_code_LT01_2_count   0.54792    0.08746   6.265 8.15e-10 ***
## category_code_LT01_4_count   0.68738    0.09162   7.502 2.95e-13 ***
## category_code_LT01_5_count   0.92455    0.06152  15.029  < 2e-16 ***
## category_code_LT01_8_count  -0.12107    0.26864  -0.451    0.652    
## category_code_LT01_14_count  0.04105    0.32129   0.128    0.898    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 492 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6368 
## F-statistic: 175.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 0.636837873098915 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9862 -0.7495  0.0485  0.8441  3.4580 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95989    0.08572 116.193  < 2e-16 ***
## category_code_LT01_2_count   0.54828    0.08753   6.264 8.20e-10 ***
## category_code_LT01_4_count   0.68870    0.09107   7.562 1.96e-13 ***
## category_code_LT01_5_count   0.92536    0.06124  15.111  < 2e-16 ***
## category_code_LT01_8_count  -0.12068    0.26864  -0.449    0.653    
## category_code_LT01_15_count  0.02896    0.73520   0.039    0.969    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 492 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6368 
## F-statistic: 175.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 0.636949021526785 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9863 -0.7499  0.0409  0.8419  3.4581 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96031    0.08571 116.208  < 2e-16 ***
## category_code_LT01_2_count   0.54441    0.08795   6.190 1.27e-09 ***
## category_code_LT01_4_count   0.69028    0.09077   7.605 1.46e-13 ***
## category_code_LT01_5_count   0.92494    0.06123  15.107  < 2e-16 ***
## category_code_LT01_8_count  -0.12591    0.26893  -0.468    0.640    
## category_code_LT01_16_count  0.44810    1.14869   0.390    0.697    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 492 degrees of freedom
## Multiple R-squared:  0.6406, Adjusted R-squared:  0.6369 
## F-statistic: 175.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 0.639047085851322 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9550 -0.7309  0.0662  0.8717  3.4000 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93694    0.08858 112.183  < 2e-16 ***
## category_code_LT01_2_count   0.52248    0.08831   5.917 6.16e-09 ***
## category_code_LT01_4_count   0.67069    0.09096   7.374 7.08e-13 ***
## category_code_LT01_5_count   0.91345    0.06052  15.095  < 2e-16 ***
## category_code_LT01_9_count   0.33671    0.22217   1.516    0.130    
## category_code_LT01_10_count  0.08559    0.11054   0.774    0.439    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 492 degrees of freedom
## Multiple R-squared:  0.6427, Adjusted R-squared:  0.639 
## F-statistic:   177 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 0.64148114932466 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9777 -0.7518  0.0781  0.8483  3.4728 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96219    0.08523 116.887  < 2e-16 ***
## category_code_LT01_2_count   0.45598    0.09498   4.801 2.10e-06 ***
## category_code_LT01_4_count   0.60726    0.09671   6.279 7.49e-10 ***
## category_code_LT01_5_count   0.90983    0.06034  15.078  < 2e-16 ***
## category_code_LT01_9_count   0.33415    0.22019   1.518   0.1298    
## category_code_LT01_11_count  0.23091    0.11627   1.986   0.0476 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 492 degrees of freedom
## Multiple R-squared:  0.6451, Adjusted R-squared:  0.6415 
## F-statistic: 178.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 0.638613446670438 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9728 -0.7463  0.0591  0.8645  3.4763 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95499    0.08549 116.440  < 2e-16 ***
## category_code_LT01_2_count   0.52746    0.08896   5.929 5.74e-09 ***
## category_code_LT01_4_count   0.67443    0.09118   7.396 6.08e-13 ***
## category_code_LT01_5_count   0.91318    0.06081  15.017  < 2e-16 ***
## category_code_LT01_9_count   0.35679    0.22077   1.616    0.107    
## category_code_LT01_12_count  0.01857    0.20196   0.092    0.927    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.354 on 492 degrees of freedom
## Multiple R-squared:  0.6422, Adjusted R-squared:  0.6386 
## F-statistic: 176.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 0.638721838248256 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9726 -0.7445  0.0600  0.8721  3.4766 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95492    0.08548 116.458  < 2e-16 ***
## category_code_LT01_2_count   0.52666    0.08813   5.976 4.40e-09 ***
## category_code_LT01_4_count   0.67137    0.09132   7.352 8.22e-13 ***
## category_code_LT01_5_count   0.91299    0.06057  15.074  < 2e-16 ***
## category_code_LT01_9_count   0.36249    0.22120   1.639    0.102    
## category_code_LT01_13_count  0.09421    0.23847   0.395    0.693    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.354 on 492 degrees of freedom
## Multiple R-squared:  0.6424, Adjusted R-squared:  0.6387 
## F-statistic: 176.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 0.63860755766467 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9732 -0.7486  0.0576  0.8720  3.4758 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.955119   0.085593 116.307  < 2e-16 ***
## category_code_LT01_2_count  0.528576   0.088084   6.001 3.81e-09 ***
## category_code_LT01_4_count  0.674914   0.091657   7.364 7.59e-13 ***
## category_code_LT01_5_count  0.913571   0.060829  15.019  < 2e-16 ***
## category_code_LT01_9_count  0.356572   0.221200   1.612    0.108    
## category_code_LT01_14_count 0.006711   0.321092   0.021    0.983    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.354 on 492 degrees of freedom
## Multiple R-squared:  0.6422, Adjusted R-squared:  0.6386 
## F-statistic: 176.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 0.638611277593956 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9733 -0.7500  0.0580  0.8728  3.4756 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95506    0.08549 116.441  < 2e-16 ***
## category_code_LT01_2_count   0.52820    0.08821   5.988 4.10e-09 ***
## category_code_LT01_4_count   0.67457    0.09119   7.398 6.03e-13 ***
## category_code_LT01_5_count   0.91376    0.06056  15.089  < 2e-16 ***
## category_code_LT01_9_count   0.35726    0.22084   1.618    0.106    
## category_code_LT01_15_count  0.05441    0.73357   0.074    0.941    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.354 on 492 degrees of freedom
## Multiple R-squared:  0.6422, Adjusted R-squared:  0.6386 
## F-statistic: 176.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 0.638681483794892 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9733 -0.7477  0.0511  0.8731  3.4758 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95536    0.08549 116.449  < 2e-16 ***
## category_code_LT01_2_count   0.52545    0.08857   5.933 5.62e-09 ***
## category_code_LT01_4_count   0.67625    0.09088   7.441 4.49e-13 ***
## category_code_LT01_5_count   0.91329    0.06056  15.081  < 2e-16 ***
## category_code_LT01_9_count   0.35470    0.22085   1.606    0.109    
## category_code_LT01_16_count  0.36407    1.14499   0.318    0.751    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.354 on 492 degrees of freedom
## Multiple R-squared:  0.6423, Adjusted R-squared:  0.6387 
## F-statistic: 176.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 0.640390827215734 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9645 -0.7362  0.0724  0.8524  3.3755 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94475    0.08851 112.355  < 2e-16 ***
## category_code_LT01_2_count   0.46444    0.09491   4.894 1.34e-06 ***
## category_code_LT01_4_count   0.61153    0.09683   6.316 6.02e-10 ***
## category_code_LT01_5_count   0.91594    0.06027  15.197  < 2e-16 ***
## category_code_LT01_10_count  0.09832    0.10963   0.897   0.3703    
## category_code_LT01_11_count  0.23685    0.11635   2.036   0.0423 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.644,  Adjusted R-squared:  0.6404 
## F-statistic:   178 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 0.637364834444846 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9587 -0.7665  0.0673  0.8529  3.3723 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93618    0.08878 111.915  < 2e-16 ***
## category_code_LT01_2_count   0.53891    0.08870   6.076 2.48e-09 ***
## category_code_LT01_4_count   0.68112    0.09122   7.467 3.77e-13 ***
## category_code_LT01_5_count   0.91998    0.06074  15.145  < 2e-16 ***
## category_code_LT01_10_count  0.10496    0.11011   0.953    0.341    
## category_code_LT01_12_count  0.01266    0.20245   0.063    0.950    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 492 degrees of freedom
## Multiple R-squared:  0.641,  Adjusted R-squared:  0.6374 
## F-statistic: 175.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 0.637413388303566 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9588 -0.7660  0.0486  0.8530  3.3728 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93629    0.08878 111.923  < 2e-16 ***
## category_code_LT01_2_count   0.53865    0.08786   6.131 1.80e-09 ***
## category_code_LT01_4_count   0.67925    0.09131   7.439 4.56e-13 ***
## category_code_LT01_5_count   0.91995    0.06050  15.206  < 2e-16 ***
## category_code_LT01_10_count  0.10444    0.11007   0.949    0.343    
## category_code_LT01_13_count  0.06301    0.23849   0.264    0.792    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 492 degrees of freedom
## Multiple R-squared:  0.6411, Adjusted R-squared:  0.6374 
## F-statistic: 175.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 0.637366897669154 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9586 -0.7684  0.0650  0.8519  3.3698 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93541    0.08925 111.319  < 2e-16 ***
## category_code_LT01_2_count   0.53993    0.08782   6.148 1.62e-09 ***
## category_code_LT01_4_count   0.68256    0.09162   7.450 4.24e-13 ***
## category_code_LT01_5_count   0.92083    0.06079  15.149  < 2e-16 ***
## category_code_LT01_10_count  0.10716    0.11256   0.952    0.342    
## category_code_LT01_14_count -0.02690    0.32837  -0.082    0.935    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 492 degrees of freedom
## Multiple R-squared:  0.641,  Adjusted R-squared:  0.6374 
## F-statistic: 175.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 0.637363126434412 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9588 -0.7675  0.0658  0.8524  3.3715 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93607    0.08881 111.878  < 2e-16 ***
## category_code_LT01_2_count   0.53991    0.08792   6.141 1.70e-09 ***
## category_code_LT01_4_count   0.68191    0.09119   7.478 3.48e-13 ***
## category_code_LT01_5_count   0.92029    0.06049  15.213  < 2e-16 ***
## category_code_LT01_10_count  0.10556    0.11037   0.956    0.339    
## category_code_LT01_15_count -0.02943    0.73682  -0.040    0.968    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 492 degrees of freedom
## Multiple R-squared:  0.641,  Adjusted R-squared:  0.6374 
## F-statistic: 175.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 0.637442430433873 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9593 -0.7648  0.0586  0.8531  3.3731 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93678    0.08879 111.910  < 2e-16 ***
## category_code_LT01_2_count   0.53636    0.08835   6.071 2.54e-09 ***
## category_code_LT01_4_count   0.68273    0.09093   7.508 2.84e-13 ***
## category_code_LT01_5_count   0.91988    0.06049  15.206  < 2e-16 ***
## category_code_LT01_10_count  0.10382    0.11011   0.943    0.346    
## category_code_LT01_16_count  0.37914    1.14726   0.330    0.741    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 492 degrees of freedom
## Multiple R-squared:  0.6411, Adjusted R-squared:  0.6374 
## F-statistic: 175.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 0.63992060451897 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9881 -0.7545  0.0772  0.8593  3.4588 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96640    0.08539 116.714  < 2e-16 ***
## category_code_LT01_2_count   0.47357    0.09471   5.000 7.99e-07 ***
## category_code_LT01_4_count   0.61651    0.09673   6.374 4.25e-10 ***
## category_code_LT01_5_count   0.91875    0.06053  15.178  < 2e-16 ***
## category_code_LT01_11_count  0.25141    0.11976   2.099   0.0363 *  
## category_code_LT01_12_count -0.08317    0.20747  -0.401   0.6887    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.351 on 492 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6399 
## F-statistic: 177.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 0.639832160210731 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9859 -0.7504  0.0798  0.8454  3.4620 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96580    0.08539 116.707  < 2e-16 ***
## category_code_LT01_2_count   0.47129    0.09466   4.979 8.87e-07 ***
## category_code_LT01_4_count   0.61505    0.09703   6.338 5.25e-10 ***
## category_code_LT01_5_count   0.91637    0.06033  15.190  < 2e-16 ***
## category_code_LT01_11_count  0.23905    0.11650   2.052   0.0407 *  
## category_code_LT01_13_count  0.04749    0.23784   0.200   0.8418    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 492 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6398 
## F-statistic: 177.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 0.639811428512661 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9861 -0.7515  0.0822  0.8571  3.4619 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96628    0.08548 116.585  < 2e-16 ***
## category_code_LT01_2_count   0.47134    0.09473   4.976 9.00e-07 ***
## category_code_LT01_4_count   0.61521    0.09755   6.307 6.35e-10 ***
## category_code_LT01_5_count   0.91599    0.06062  15.111  < 2e-16 ***
## category_code_LT01_11_count  0.23999    0.11639   2.062   0.0397 *  
## category_code_LT01_14_count  0.03437    0.31994   0.107   0.9145    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 492 degrees of freedom
## Multiple R-squared:  0.6434, Adjusted R-squared:  0.6398 
## F-statistic: 177.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 0.639805292302482 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9860 -0.7534  0.0815  0.8557  3.4617 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96584    0.08539 116.703  < 2e-16 ***
## category_code_LT01_2_count   0.47204    0.09472   4.984 8.66e-07 ***
## category_code_LT01_4_count   0.61692    0.09695   6.363 4.53e-10 ***
## category_code_LT01_5_count   0.91658    0.06032  15.194  < 2e-16 ***
## category_code_LT01_11_count  0.24036    0.11650   2.063   0.0396 *  
## category_code_LT01_15_count -0.04120    0.73284  -0.056   0.9552    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 492 degrees of freedom
## Multiple R-squared:  0.6434, Adjusted R-squared:  0.6398 
## F-statistic: 177.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 0.639909418075598 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9861 -0.7514  0.0813  0.8562  3.4619 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96623    0.08539 116.718  < 2e-16 ***
## category_code_LT01_2_count   0.46773    0.09522   4.912 1.23e-06 ***
## category_code_LT01_4_count   0.61767    0.09677   6.383 4.03e-10 ***
## category_code_LT01_5_count   0.91610    0.06032  15.187  < 2e-16 ***
## category_code_LT01_11_count  0.24035    0.11637   2.065   0.0394 *  
## category_code_LT01_16_count  0.43571    1.14253   0.381   0.7031    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 492 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6399 
## F-statistic: 177.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 0.636755891061432 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9813 -0.7481  0.0448  0.8388  3.4650 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95857    0.08568 116.223  < 2e-16 ***
## category_code_LT01_2_count   0.54628    0.08841   6.179 1.36e-09 ***
## category_code_LT01_4_count   0.68466    0.09151   7.482 3.40e-13 ***
## category_code_LT01_5_count   0.92022    0.06081  15.134  < 2e-16 ***
## category_code_LT01_12_count  0.01838    0.20253   0.091    0.928    
## category_code_LT01_13_count  0.06853    0.23869   0.287    0.774    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 492 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.6368 
## F-statistic: 175.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 0.636704732188782 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9816 -0.7486  0.0489  0.8368  3.4648 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95906    0.08579 116.093  < 2e-16 ***
## category_code_LT01_2_count   0.54699    0.08841   6.187 1.29e-09 ***
## category_code_LT01_4_count   0.68582    0.09190   7.462 3.88e-13 ***
## category_code_LT01_5_count   0.91995    0.06106  15.065  < 2e-16 ***
## category_code_LT01_12_count  0.01809    0.20298   0.089    0.929    
## category_code_LT01_14_count  0.03691    0.32208   0.115    0.909    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 492 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.6367 
## F-statistic: 175.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 0.636696009452769 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9816 -0.7482  0.0426  0.8474  3.4645 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95862    0.08569 116.213  < 2e-16 ***
## category_code_LT01_2_count   0.54719    0.08854   6.180 1.35e-09 ***
## category_code_LT01_4_count   0.68693    0.09144   7.512 2.76e-13 ***
## category_code_LT01_5_count   0.92064    0.06080  15.141  < 2e-16 ***
## category_code_LT01_12_count  0.01986    0.20255   0.098    0.922    
## category_code_LT01_15_count  0.02673    0.73548   0.036    0.971    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 492 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.6367 
## F-statistic: 175.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 0.636795138625374 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9816 -0.7485  0.0422  0.8459  3.4648 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95895    0.08569 116.227  < 2e-16 ***
## category_code_LT01_2_count   0.54347    0.08897   6.109 2.04e-09 ***
## category_code_LT01_4_count   0.68833    0.09112   7.554 2.07e-13 ***
## category_code_LT01_5_count   0.92005    0.06081  15.131  < 2e-16 ***
## category_code_LT01_12_count  0.02092    0.20250   0.103    0.918    
## category_code_LT01_16_count  0.42259    1.14759   0.368    0.713    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 492 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.6368 
## F-statistic: 175.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 0.636760826089038 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9817 -0.7487  0.0452  0.8367  3.4647 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95910    0.08578 116.107  < 2e-16 ***
## category_code_LT01_2_count   0.54689    0.08757   6.245 9.17e-10 ***
## category_code_LT01_4_count   0.68380    0.09207   7.427 4.93e-13 ***
## category_code_LT01_5_count   0.91998    0.06085  15.118  < 2e-16 ***
## category_code_LT01_13_count  0.06913    0.23862   0.290    0.772    
## category_code_LT01_14_count  0.03924    0.32129   0.122    0.903    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 492 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.6368 
## F-statistic: 175.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 0.636751895140679 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9817 -0.7482  0.0377  0.8457  3.4643 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95863    0.08568 116.224  < 2e-16 ***
## category_code_LT01_2_count   0.54713    0.08766   6.241 9.37e-10 ***
## category_code_LT01_4_count   0.68492    0.09157   7.480 3.45e-13 ***
## category_code_LT01_5_count   0.92078    0.06055  15.206  < 2e-16 ***
## category_code_LT01_13_count  0.06985    0.23914   0.292    0.770    
## category_code_LT01_15_count  0.03913    0.73681   0.053    0.958    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 492 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.6368 
## F-statistic: 175.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 0.636855433458738 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9817 -0.7485  0.0373  0.8484  3.4647 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95897    0.08568 116.239  < 2e-16 ***
## category_code_LT01_2_count   0.54342    0.08808   6.169 1.43e-09 ***
## category_code_LT01_4_count   0.68643    0.09120   7.527 2.50e-13 ***
## category_code_LT01_5_count   0.92017    0.06056  15.195  < 2e-16 ***
## category_code_LT01_13_count  0.07257    0.23878   0.304    0.761    
## category_code_LT01_16_count  0.43435    1.14822   0.378    0.705    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 492 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6369 
## F-statistic: 175.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 0.636699677311834 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9820 -0.7487  0.0429  0.8364  3.4642 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95915    0.08578 116.096  < 2e-16 ***
## category_code_LT01_2_count   0.54794    0.08767   6.250 8.89e-10 ***
## category_code_LT01_4_count   0.68620    0.09195   7.463 3.88e-13 ***
## category_code_LT01_5_count   0.92045    0.06085  15.127  < 2e-16 ***
## category_code_LT01_14_count  0.03880    0.32133   0.121    0.904    
## category_code_LT01_15_count  0.02436    0.73531   0.033    0.974    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 492 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.6367 
## F-statistic: 175.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 0.636802010767069 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9820 -0.7491  0.0426  0.8372  3.4645 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95957    0.08578 116.108  < 2e-16 ***
## category_code_LT01_2_count   0.54411    0.08812   6.174 1.39e-09 ***
## category_code_LT01_4_count   0.68737    0.09164   7.501 2.98e-13 ***
## category_code_LT01_5_count   0.91976    0.06086  15.113  < 2e-16 ***
## category_code_LT01_14_count  0.04548    0.32175   0.141    0.888    
## category_code_LT01_16_count  0.42954    1.14915   0.374    0.709    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 492 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6368 
## F-statistic: 175.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 0.636788893974258 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9821 -0.7486  0.0334  0.8452  3.4641 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95902    0.08569 116.227  < 2e-16 ***
## category_code_LT01_2_count   0.54456    0.08819   6.175 1.39e-09 ***
## category_code_LT01_4_count   0.68880    0.09110   7.561 1.97e-13 ***
## category_code_LT01_5_count   0.92068    0.06055  15.205  < 2e-16 ***
## category_code_LT01_15_count  0.03459    0.73565   0.047    0.963    
## category_code_LT01_16_count  0.42254    1.14815   0.368    0.713    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 492 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.6368 
## F-statistic: 175.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 0.617769632709485 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0283 -0.7691 -0.0337  0.9746  3.8214 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97959    0.08794 113.479  < 2e-16 ***
## category_code_LT01_2_count  0.78934    0.07617  10.363  < 2e-16 ***
## category_code_LT01_5_count  0.95768    0.06257  15.306  < 2e-16 ***
## category_code_LT01_6_count  0.50622    0.15181   3.335 0.000919 ***
## category_code_LT01_7_count  0.64109    0.15095   4.247 2.59e-05 ***
## category_code_LT01_8_count -0.15734    0.27597  -0.570 0.568848    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.6178 
## F-statistic: 161.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 0.619411479758865 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0143 -0.7881  0.0090  0.9884  3.8267 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97430    0.08775 113.672  < 2e-16 ***
## category_code_LT01_2_count  0.76917    0.07716   9.968  < 2e-16 ***
## category_code_LT01_5_count  0.94520    0.06193  15.263  < 2e-16 ***
## category_code_LT01_6_count  0.48945    0.15156   3.229  0.00132 ** 
## category_code_LT01_7_count  0.61216    0.15142   4.043 6.13e-05 ***
## category_code_LT01_9_count  0.35590    0.22743   1.565  0.11825    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6232, Adjusted R-squared:  0.6194 
## F-statistic: 162.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 0.617770010844134 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0095 -0.7802 -0.0189  0.9871  3.8365 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96441    0.09110 109.376  < 2e-16 ***
## category_code_LT01_2_count   0.78639    0.07644  10.288  < 2e-16 ***
## category_code_LT01_5_count   0.95255    0.06189  15.391  < 2e-16 ***
## category_code_LT01_6_count   0.48852    0.15359   3.181  0.00156 ** 
## category_code_LT01_7_count   0.63065    0.15139   4.166 3.66e-05 ***
## category_code_LT01_10_count  0.06536    0.11456   0.571  0.56856    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.6178 
## F-statistic: 161.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 0.62391741405055 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0242 -0.7353  0.0059  0.9316  3.8153 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98565    0.08723 114.473  < 2e-16 ***
## category_code_LT01_2_count   0.65272    0.08923   7.315 1.05e-12 ***
## category_code_LT01_5_count   0.94301    0.06148  15.339  < 2e-16 ***
## category_code_LT01_6_count   0.42719    0.15266   2.798  0.00534 ** 
## category_code_LT01_7_count   0.50691    0.15633   3.243  0.00127 ** 
## category_code_LT01_11_count  0.34090    0.11781   2.894  0.00398 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 492 degrees of freedom
## Multiple R-squared:  0.6277, Adjusted R-squared:  0.6239 
## F-statistic: 165.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 0.617583516040926 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0219 -0.7912 -0.0229  0.9782  3.8230 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97797    0.08792 113.484  < 2e-16 ***
## category_code_LT01_2_count   0.78581    0.07761  10.125  < 2e-16 ***
## category_code_LT01_5_count   0.95077    0.06217  15.293  < 2e-16 ***
## category_code_LT01_6_count   0.49731    0.15269   3.257   0.0012 ** 
## category_code_LT01_7_count   0.63726    0.15090   4.223 2.87e-05 ***
## category_code_LT01_12_count  0.06089    0.20832   0.292   0.7702    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6176 
## F-statistic: 161.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 0.617676467917144 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0222 -0.7849 -0.0159  0.9784  3.8232 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97778    0.08791 113.494  < 2e-16 ***
## category_code_LT01_2_count   0.78691    0.07650  10.286  < 2e-16 ***
## category_code_LT01_5_count   0.95158    0.06193  15.366  < 2e-16 ***
## category_code_LT01_6_count   0.50274    0.15168   3.314 0.000986 ***
## category_code_LT01_7_count   0.62863    0.15226   4.129 4.29e-05 ***
## category_code_LT01_13_count  0.11133    0.24583   0.453 0.650850    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6215, Adjusted R-squared:  0.6177 
## F-statistic: 161.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 0.618268334561126 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0206 -0.7824  0.0089  0.9720  3.8200 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98097    0.08789 113.557  < 2e-16 ***
## category_code_LT01_2_count   0.77677    0.07731  10.048  < 2e-16 ***
## category_code_LT01_5_count   0.94463    0.06236  15.149  < 2e-16 ***
## category_code_LT01_6_count   0.51352    0.15198   3.379 0.000786 ***
## category_code_LT01_7_count   0.62312    0.15150   4.113 4.58e-05 ***
## category_code_LT01_14_count  0.32330    0.32857   0.984 0.325605    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6183 
## F-statistic:   162 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 0.617741532273401 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0235 -0.7782 -0.0325  0.9755  3.8227 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97822    0.08791 113.511  < 2e-16 ***
## category_code_LT01_2_count   0.78478    0.07681  10.217  < 2e-16 ***
## category_code_LT01_5_count   0.95269    0.06189  15.392  < 2e-16 ***
## category_code_LT01_6_count   0.49766    0.15192   3.276  0.00113 ** 
## category_code_LT01_7_count   0.63904    0.15087   4.236 2.72e-05 ***
## category_code_LT01_15_count  0.40452    0.75266   0.537  0.59120    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.6177 
## F-statistic: 161.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 0.617727532695089 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0227 -0.7936 -0.0194  0.9766  3.8226 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97839    0.08791 113.508  < 2e-16 ***
## category_code_LT01_2_count   0.78366    0.07717  10.155  < 2e-16 ***
## category_code_LT01_5_count   0.95138    0.06193  15.363  < 2e-16 ***
## category_code_LT01_6_count   0.51006    0.15238   3.347 0.000879 ***
## category_code_LT01_7_count   0.63937    0.15088   4.238  2.7e-05 ***
## category_code_LT01_16_count  0.61529    1.18230   0.520 0.603009    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.6177 
## F-statistic: 161.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 0.606950726371269 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0343 -0.8250  0.0167  0.9826  3.8246 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97636    0.08921 111.831  < 2e-16 ***
## category_code_LT01_2_count  0.87355    0.07386  11.827  < 2e-16 ***
## category_code_LT01_5_count  0.97104    0.06340  15.316  < 2e-16 ***
## category_code_LT01_6_count  0.51271    0.15408   3.327 0.000942 ***
## category_code_LT01_8_count -0.13366    0.27983  -0.478 0.633096    
## category_code_LT01_9_count  0.45971    0.22989   2.000 0.046080 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.412 on 492 degrees of freedom
## Multiple R-squared:  0.6109, Adjusted R-squared:  0.607 
## F-statistic: 154.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 0.604432919964143 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0237 -0.8061 -0.0140  0.9768  3.8421 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95889    0.09269 107.440  < 2e-16 ***
## category_code_LT01_2_count   0.89846    0.07276  12.347  < 2e-16 ***
## category_code_LT01_5_count   0.98090    0.06340  15.471  < 2e-16 ***
## category_code_LT01_6_count   0.50728    0.15634   3.245  0.00126 ** 
## category_code_LT01_8_count  -0.11920    0.28060  -0.425  0.67116    
## category_code_LT01_10_count  0.10656    0.11615   0.918  0.35933    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 492 degrees of freedom
## Multiple R-squared:  0.6084, Adjusted R-squared:  0.6044 
## F-statistic: 152.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 0.615972835957091 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0416 -0.8154  0.0316  0.9327  3.8442 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99044    0.08818 113.297  < 2e-16 ***
## category_code_LT01_2_count   0.69331    0.08929   7.765 4.77e-14 ***
## category_code_LT01_5_count   0.96118    0.06267  15.336  < 2e-16 ***
## category_code_LT01_6_count   0.42352    0.15443   2.742  0.00632 ** 
## category_code_LT01_8_count  -0.09513    0.27648  -0.344  0.73094    
## category_code_LT01_11_count  0.45086    0.11396   3.956 8.73e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 492 degrees of freedom
## Multiple R-squared:  0.6198, Adjusted R-squared:  0.616 
## F-statistic: 160.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 0.603863493579496 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0445 -0.8282 -0.0334  0.9672  3.8199 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98105    0.08953 111.486  < 2e-16 ***
## category_code_LT01_2_count   0.90108    0.07391  12.191  < 2e-16 ***
## category_code_LT01_5_count   0.97899    0.06370  15.370  < 2e-16 ***
## category_code_LT01_6_count   0.52383    0.15543   3.370  0.00081 ***
## category_code_LT01_8_count  -0.11806    0.28093  -0.420  0.67450    
## category_code_LT01_12_count  0.07748    0.21213   0.365  0.71510    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 492 degrees of freedom
## Multiple R-squared:  0.6078, Adjusted R-squared:  0.6039 
## F-statistic: 152.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 0.604531036032555 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0430 -0.8160 -0.0369  0.9711  3.8206 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98031    0.08946 111.567  < 2e-16 ***
## category_code_LT01_2_count   0.89596    0.07302  12.269  < 2e-16 ***
## category_code_LT01_5_count   0.97784    0.06348  15.404  < 2e-16 ***
## category_code_LT01_6_count   0.52983    0.15431   3.434 0.000646 ***
## category_code_LT01_8_count  -0.09934    0.28094  -0.354 0.723783    
## category_code_LT01_13_count  0.24361    0.24811   0.982 0.326640    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 492 degrees of freedom
## Multiple R-squared:  0.6085, Adjusted R-squared:  0.6045 
## F-statistic: 152.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 0.605296807811043 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0421 -0.8258 -0.0003  0.9409  3.8157 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98529    0.08941 111.674  < 2e-16 ***
## category_code_LT01_2_count   0.88382    0.07400  11.944  < 2e-16 ***
## category_code_LT01_5_count   0.96936    0.06389  15.172  < 2e-16 ***
## category_code_LT01_6_count   0.54549    0.15455   3.530 0.000455 ***
## category_code_LT01_8_count  -0.12282    0.28031  -0.438 0.661471    
## category_code_LT01_14_count  0.46082    0.33252   1.386 0.166429    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 492 degrees of freedom
## Multiple R-squared:  0.6093, Adjusted R-squared:  0.6053 
## F-statistic: 153.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 0.603938405423157 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0464 -0.8013 -0.0030  0.9700  3.8197 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98129    0.08952 111.499  < 2e-16 ***
## category_code_LT01_2_count   0.90211    0.07291  12.374  < 2e-16 ***
## category_code_LT01_5_count   0.98134    0.06345  15.467  < 2e-16 ***
## category_code_LT01_6_count   0.52606    0.15467   3.401 0.000726 ***
## category_code_LT01_8_count  -0.11596    0.28075  -0.413 0.679758    
## category_code_LT01_15_count  0.36458    0.76610   0.476 0.634366    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 492 degrees of freedom
## Multiple R-squared:  0.6079, Adjusted R-squared:  0.6039 
## F-statistic: 152.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 0.603925234732303 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0459 -0.8177 -0.0045  0.9715  3.8194 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98151    0.08952 111.496  < 2e-16 ***
## category_code_LT01_2_count   0.90117    0.07327  12.299  < 2e-16 ***
## category_code_LT01_5_count   0.98037    0.06346  15.448  < 2e-16 ***
## category_code_LT01_6_count   0.53736    0.15521   3.462 0.000582 ***
## category_code_LT01_8_count  -0.12153    0.28116  -0.432 0.665740    
## category_code_LT01_16_count  0.55237    1.20508   0.458 0.646891    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 492 degrees of freedom
## Multiple R-squared:  0.6079, Adjusted R-squared:  0.6039 
## F-statistic: 152.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 0.607147594879868 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0135 -0.8254  0.0113  0.9696  3.8425 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95849    0.09235 107.838  < 2e-16 ***
## category_code_LT01_2_count   0.86909    0.07418  11.716  < 2e-16 ***
## category_code_LT01_5_count   0.96678    0.06269  15.421  < 2e-16 ***
## category_code_LT01_6_count   0.49283    0.15579   3.164  0.00166 ** 
## category_code_LT01_9_count   0.43760    0.23123   1.892  0.05901 .  
## category_code_LT01_10_count  0.08028    0.11650   0.689  0.49109    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.412 on 492 degrees of freedom
## Multiple R-squared:  0.6111, Adjusted R-squared:  0.6071 
## F-statistic: 154.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 0.618222070433971 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0279 -0.8152  0.0331  0.9156  3.9159 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98497    0.08792 113.568  < 2e-16 ***
## category_code_LT01_2_count   0.67126    0.08991   7.466 3.78e-13 ***
## category_code_LT01_5_count   0.94938    0.06196  15.322  < 2e-16 ***
## category_code_LT01_6_count   0.40881    0.15396   2.655 0.008181 ** 
## category_code_LT01_9_count   0.39433    0.22700   1.737 0.082987 .  
## category_code_LT01_11_count  0.43758    0.11390   3.842 0.000138 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6182 
## F-statistic:   162 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 0.606862454287677 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0284 -0.8376  0.0128  0.9747  3.8260 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97498    0.08918 111.851  < 2e-16 ***
## category_code_LT01_2_count   0.86873    0.07546  11.513  < 2e-16 ***
## category_code_LT01_5_count   0.96456    0.06299  15.313  < 2e-16 ***
## category_code_LT01_6_count   0.50343    0.15496   3.249  0.00124 ** 
## category_code_LT01_9_count   0.45558    0.22978   1.983  0.04796 *  
## category_code_LT01_12_count  0.07244    0.21120   0.343  0.73175    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.412 on 492 degrees of freedom
## Multiple R-squared:  0.6108, Adjusted R-squared:  0.6069 
## F-statistic: 154.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 0.607765522682003 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0267 -0.8214  0.0175  0.9766  3.8268 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97416    0.08908 111.966   <2e-16 ***
## category_code_LT01_2_count   0.86070    0.07473  11.517   <2e-16 ***
## category_code_LT01_5_count   0.96321    0.06271  15.359   <2e-16 ***
## category_code_LT01_6_count   0.50891    0.15378   3.309   0.0010 ** 
## category_code_LT01_9_count   0.47014    0.22986   2.045   0.0414 *  
## category_code_LT01_13_count  0.27634    0.24710   1.118   0.2640    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.411 on 492 degrees of freedom
## Multiple R-squared:  0.6117, Adjusted R-squared:  0.6078 
## F-statistic:   155 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 0.607974275387115 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0268 -0.8228  0.0335  0.9600  3.8220 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97894    0.08911 111.986  < 2e-16 ***
## category_code_LT01_2_count   0.85527    0.07532  11.356  < 2e-16 ***
## category_code_LT01_5_count   0.95648    0.06316  15.144  < 2e-16 ***
## category_code_LT01_6_count   0.52370    0.15417   3.397 0.000737 ***
## category_code_LT01_9_count   0.43386    0.23015   1.885 0.060007 .  
## category_code_LT01_14_count  0.40882    0.33233   1.230 0.219218    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.41 on 492 degrees of freedom
## Multiple R-squared:  0.6119, Adjusted R-squared:  0.608 
## F-statistic: 155.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 0.606979093771281 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0302 -0.8295  0.0052  0.9794  3.8257 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97522    0.08917 111.870  < 2e-16 ***
## category_code_LT01_2_count   0.86883    0.07454  11.656  < 2e-16 ***
## category_code_LT01_5_count   0.96679    0.06270  15.418  < 2e-16 ***
## category_code_LT01_6_count   0.50487    0.15420   3.274  0.00113 ** 
## category_code_LT01_9_count   0.45833    0.22979   1.995  0.04664 *  
## category_code_LT01_15_count  0.39195    0.76327   0.514  0.60782    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.412 on 492 degrees of freedom
## Multiple R-squared:  0.6109, Adjusted R-squared:  0.607 
## F-statistic: 154.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 0.60687817718527 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0298 -0.8382  0.0093  0.9763  3.8256 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97536    0.08918 111.854  < 2e-16 ***
## category_code_LT01_2_count   0.86973    0.07476  11.633  < 2e-16 ***
## category_code_LT01_5_count   0.96591    0.06274  15.396  < 2e-16 ***
## category_code_LT01_6_count   0.51520    0.15472   3.330 0.000934 ***
## category_code_LT01_9_count   0.45308    0.22990   1.971 0.049311 *  
## category_code_LT01_16_count  0.44449    1.19944   0.371 0.711109    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.412 on 492 degrees of freedom
## Multiple R-squared:  0.6108, Adjusted R-squared:  0.6069 
## F-statistic: 154.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 0.616396312757027 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0188 -0.8156  0.0340  0.9336  3.9082 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97000    0.09130 109.196  < 2e-16 ***
## category_code_LT01_2_count   0.68709    0.08954   7.673 9.07e-14 ***
## category_code_LT01_5_count   0.95777    0.06191  15.469  < 2e-16 ***
## category_code_LT01_6_count   0.40143    0.15603   2.573   0.0104 *  
## category_code_LT01_10_count  0.09306    0.11440   0.813   0.4164    
## category_code_LT01_11_count  0.44897    0.11393   3.941 9.30e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 492 degrees of freedom
## Multiple R-squared:  0.6203, Adjusted R-squared:  0.6164 
## F-statistic: 160.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 0.604374568766433 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0186 -0.8063 -0.0152  0.9650  3.8430 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95800    0.09267 107.455   <2e-16 ***
## category_code_LT01_2_count   0.89367    0.07437  12.017   <2e-16 ***
## category_code_LT01_5_count   0.97489    0.06296  15.484   <2e-16 ***
## category_code_LT01_6_count   0.49885    0.15715   3.174   0.0016 ** 
## category_code_LT01_10_count  0.10471    0.11617   0.901   0.3679    
## category_code_LT01_12_count  0.06961    0.21193   0.328   0.7427    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 492 degrees of freedom
## Multiple R-squared:  0.6084, Adjusted R-squared:  0.6044 
## F-statistic: 152.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 0.605047641607269 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0182 -0.8050 -0.0282  0.9846  3.8429 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95804    0.09259 107.547  < 2e-16 ***
## category_code_LT01_2_count   0.88828    0.07349  12.087  < 2e-16 ***
## category_code_LT01_5_count   0.97420    0.06269  15.540  < 2e-16 ***
## category_code_LT01_6_count   0.50530    0.15608   3.237  0.00129 ** 
## category_code_LT01_10_count  0.10180    0.11610   0.877  0.38103    
## category_code_LT01_13_count  0.24100    0.24772   0.973  0.33108    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 492 degrees of freedom
## Multiple R-squared:  0.609,  Adjusted R-squared:  0.605 
## F-statistic: 153.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 0.60543809136388 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0232 -0.8158 -0.0072  0.9540  3.8325 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96849    0.09297 107.226  < 2e-16 ***
## category_code_LT01_2_count   0.88092    0.07417  11.877  < 2e-16 ***
## category_code_LT01_5_count   0.96631    0.06321  15.286  < 2e-16 ***
## category_code_LT01_6_count   0.52505    0.15695   3.345 0.000884 ***
## category_code_LT01_10_count  0.07237    0.11926   0.607 0.544258    
## category_code_LT01_14_count  0.40935    0.34180   1.198 0.231636    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 492 degrees of freedom
## Multiple R-squared:  0.6094, Adjusted R-squared:  0.6054 
## F-statistic: 153.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 0.604419271344644 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0209 -0.8043 -0.0237  0.9788  3.8422 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95878    0.09269 107.441  < 2e-16 ***
## category_code_LT01_2_count   0.89501    0.07334  12.204  < 2e-16 ***
## category_code_LT01_5_count   0.97707    0.06268  15.587  < 2e-16 ***
## category_code_LT01_6_count   0.50166    0.15636   3.208  0.00142 ** 
## category_code_LT01_10_count  0.10212    0.11646   0.877  0.38099    
## category_code_LT01_15_count  0.31043    0.76776   0.404  0.68614    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 492 degrees of freedom
## Multiple R-squared:  0.6084, Adjusted R-squared:  0.6044 
## F-statistic: 152.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 0.604409157457756 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0201 -0.8073 -0.0258  0.9677  3.8423 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95866    0.09269 107.444  < 2e-16 ***
## category_code_LT01_2_count   0.89415    0.07370  12.132  < 2e-16 ***
## category_code_LT01_5_count   0.97608    0.06271  15.564  < 2e-16 ***
## category_code_LT01_6_count   0.51088    0.15707   3.253  0.00122 ** 
## category_code_LT01_10_count  0.10329    0.11629   0.888  0.37486    
## category_code_LT01_16_count  0.46778    1.20417   0.388  0.69784    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 492 degrees of freedom
## Multiple R-squared:  0.6084, Adjusted R-squared:  0.6044 
## F-statistic: 152.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 0.616160591783049 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0410 -0.7858  0.0255  0.9407  3.8357 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99010    0.08812 113.365  < 2e-16 ***
## category_code_LT01_2_count   0.69470    0.08930   7.779 4.32e-14 ***
## category_code_LT01_5_count   0.96080    0.06212  15.467  < 2e-16 ***
## category_code_LT01_6_count   0.42784    0.15464   2.767  0.00588 ** 
## category_code_LT01_11_count  0.46819    0.11725   3.993 7.52e-05 ***
## category_code_LT01_12_count -0.12872    0.21479  -0.599  0.54928    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 492 degrees of freedom
## Multiple R-squared:   0.62,  Adjusted R-squared:  0.6162 
## F-statistic: 160.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 0.616274705379674 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0366 -0.8258  0.0329  0.9381  3.8575 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98891    0.08811 113.369  < 2e-16 ***
## category_code_LT01_2_count   0.68837    0.08950   7.691 7.99e-14 ***
## category_code_LT01_5_count   0.95627    0.06197  15.432  < 2e-16 ***
## category_code_LT01_6_count   0.42244    0.15421   2.739 0.006378 ** 
## category_code_LT01_11_count  0.44522    0.11425   3.897 0.000111 ***
## category_code_LT01_13_count  0.17403    0.24477   0.711 0.477421    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 492 degrees of freedom
## Multiple R-squared:  0.6201, Adjusted R-squared:  0.6163 
## F-statistic: 160.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 0.616862255612012 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0351 -0.8102  0.0328  0.9404  3.8557 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99260    0.08808 113.449  < 2e-16 ***
## category_code_LT01_2_count   0.67901    0.09006   7.539 2.29e-13 ***
## category_code_LT01_5_count   0.94873    0.06241  15.201  < 2e-16 ***
## category_code_LT01_6_count   0.43511    0.15459   2.815 0.005079 ** 
## category_code_LT01_11_count  0.44260    0.11409   3.879 0.000119 ***
## category_code_LT01_14_count  0.36868    0.32834   1.123 0.262049    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.6169 
## F-statistic:   161 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 0.615921349103226 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0386 -0.8269  0.0289  0.9346  3.8542 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98956    0.08815 113.330  < 2e-16 ***
## category_code_LT01_2_count   0.69169    0.08951   7.728 6.21e-14 ***
## category_code_LT01_5_count   0.95811    0.06196  15.464  < 2e-16 ***
## category_code_LT01_6_count   0.41936    0.15443   2.716  0.00685 ** 
## category_code_LT01_11_count  0.44991    0.11418   3.940 9.32e-05 ***
## category_code_LT01_15_count  0.17305    0.75588   0.229  0.81901    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 492 degrees of freedom
## Multiple R-squared:  0.6198, Adjusted R-squared:  0.6159 
## F-statistic: 160.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 0.616036774570058 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0381 -0.8269  0.0310  0.9366  3.8508 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98982    0.08813 113.347  < 2e-16 ***
## category_code_LT01_2_count   0.68772    0.09009   7.634 1.19e-13 ***
## category_code_LT01_5_count   0.95705    0.06197  15.443  < 2e-16 ***
## category_code_LT01_6_count   0.42762    0.15496   2.760    0.006 ** 
## category_code_LT01_11_count  0.45163    0.11394   3.964 8.47e-05 ***
## category_code_LT01_16_count  0.53026    1.18472   0.448    0.655    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 492 degrees of freedom
## Multiple R-squared:  0.6199, Adjusted R-squared:  0.616 
## F-statistic: 160.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 0.604512595685052 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0382 -0.8269 -0.0295  0.9678  3.8217 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97922    0.08942 111.605  < 2e-16 ***
## category_code_LT01_2_count   0.89103    0.07460  11.945  < 2e-16 ***
## category_code_LT01_5_count   0.97253    0.06300  15.436  < 2e-16 ***
## category_code_LT01_6_count   0.52166    0.15517   3.362 0.000835 ***
## category_code_LT01_12_count  0.06772    0.21193   0.320 0.749467    
## category_code_LT01_13_count  0.24592    0.24786   0.992 0.321604    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 492 degrees of freedom
## Multiple R-squared:  0.6085, Adjusted R-squared:  0.6045 
## F-statistic: 152.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 0.605185008585264 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0370 -0.8312 -0.0101  0.9463  3.8170 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98392    0.08939 111.694  < 2e-16 ***
## category_code_LT01_2_count   0.88092    0.07534  11.693  < 2e-16 ***
## category_code_LT01_5_count   0.96407    0.06342  15.201  < 2e-16 ***
## category_code_LT01_6_count   0.53799    0.15554   3.459  0.00059 ***
## category_code_LT01_12_count  0.04874    0.21250   0.229  0.81869    
## category_code_LT01_14_count  0.45085    0.33382   1.351  0.17746    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 492 degrees of freedom
## Multiple R-squared:  0.6092, Adjusted R-squared:  0.6052 
## F-statistic: 153.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 0.603906006509694 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0409 -0.8246 -0.0342  0.9662  3.8209 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98004    0.08948 111.532  < 2e-16 ***
## category_code_LT01_2_count   0.89663    0.07460  12.020  < 2e-16 ***
## category_code_LT01_5_count   0.97525    0.06300  15.480  < 2e-16 ***
## category_code_LT01_6_count   0.51669    0.15556   3.321 0.000962 ***
## category_code_LT01_12_count  0.07655    0.21204   0.361 0.718231    
## category_code_LT01_15_count  0.36703    0.76627   0.479 0.632164    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 492 degrees of freedom
## Multiple R-squared:  0.6079, Adjusted R-squared:  0.6039 
## F-statistic: 152.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 0.603875899386529 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0403 -0.8283 -0.0359  0.9645  3.8208 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98018    0.08949 111.527  < 2e-16 ***
## category_code_LT01_2_count   0.89609    0.07493  11.960  < 2e-16 ***
## category_code_LT01_5_count   0.97417    0.06303  15.454  < 2e-16 ***
## category_code_LT01_6_count   0.52769    0.15602   3.382 0.000776 ***
## category_code_LT01_12_count  0.07512    0.21201   0.354 0.723241    
## category_code_LT01_16_count  0.52731    1.20338   0.438 0.661439    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 492 degrees of freedom
## Multiple R-squared:  0.6079, Adjusted R-squared:  0.6039 
## F-statistic: 152.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 0.605928468937953 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0355 -0.8125 -0.0098  0.9451  3.8176 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98334    0.08930 111.792  < 2e-16 ***
## category_code_LT01_2_count   0.87343    0.07472  11.689  < 2e-16 ***
## category_code_LT01_5_count   0.96265    0.06321  15.231  < 2e-16 ***
## category_code_LT01_6_count   0.54216    0.15425   3.515 0.000481 ***
## category_code_LT01_13_count  0.24494    0.24731   0.990 0.322460    
## category_code_LT01_14_count  0.45429    0.33220   1.368 0.172078    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.414 on 492 degrees of freedom
## Multiple R-squared:  0.6099, Adjusted R-squared:  0.6059 
## F-statistic: 153.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 0.604655230302134 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0399 -0.8146 -0.0364  0.9728  3.8215 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97946    0.08940 111.628  < 2e-16 ***
## category_code_LT01_2_count   0.89038    0.07375  12.072  < 2e-16 ***
## category_code_LT01_5_count   0.97460    0.06272  15.539  < 2e-16 ***
## category_code_LT01_6_count   0.52264    0.15438   3.386 0.000767 ***
## category_code_LT01_13_count  0.25578    0.24809   1.031 0.303042    
## category_code_LT01_15_count  0.40537    0.76657   0.529 0.597178    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 492 degrees of freedom
## Multiple R-squared:  0.6086, Adjusted R-squared:  0.6047 
## F-statistic:   153 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 0.604614866240023 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0392 -0.8227 -0.0362  0.9730  3.8213 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97962    0.08941 111.622  < 2e-16 ***
## category_code_LT01_2_count   0.88983    0.07411  12.008  < 2e-16 ***
## category_code_LT01_5_count   0.97340    0.06276  15.510  < 2e-16 ***
## category_code_LT01_6_count   0.53458    0.15487   3.452 0.000605 ***
## category_code_LT01_13_count  0.25349    0.24793   1.022 0.307089    
## category_code_LT01_16_count  0.57631    1.20331   0.479 0.632196    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 492 degrees of freedom
## Multiple R-squared:  0.6086, Adjusted R-squared:  0.6046 
## F-statistic:   153 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 0.605297254200266 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0383 -0.8191  0.0009  0.9456  3.8168 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98416    0.08937 111.715  < 2e-16 ***
## category_code_LT01_2_count   0.88004    0.07458  11.799  < 2e-16 ***
## category_code_LT01_5_count   0.96559    0.06321  15.277  < 2e-16 ***
## category_code_LT01_6_count   0.53830    0.15465   3.481 0.000544 ***
## category_code_LT01_14_count  0.45414    0.33254   1.366 0.172672    
## category_code_LT01_15_count  0.33565    0.76497   0.439 0.661011    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 492 degrees of freedom
## Multiple R-squared:  0.6093, Adjusted R-squared:  0.6053 
## F-statistic: 153.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 0.605366984040104 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0375 -0.8211 -0.0095  0.9404  3.8164 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98451    0.08937 111.724  < 2e-16 ***
## category_code_LT01_2_count   0.87714    0.07517  11.669  < 2e-16 ***
## category_code_LT01_5_count   0.96392    0.06325  15.241  < 2e-16 ***
## category_code_LT01_6_count   0.55068    0.15518   3.549 0.000424 ***
## category_code_LT01_14_count  0.46938    0.33315   1.409 0.159496    
## category_code_LT01_16_count  0.63638    1.20372   0.529 0.597268    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 492 degrees of freedom
## Multiple R-squared:  0.6093, Adjusted R-squared:  0.6054 
## F-statistic: 153.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 0.603964735022997 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0422 -0.8238 -0.0349  0.9713  3.8205 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98046    0.08948 111.543  < 2e-16 ***
## category_code_LT01_2_count   0.89669    0.07397  12.123  < 2e-16 ***
## category_code_LT01_5_count   0.97651    0.06275  15.562  < 2e-16 ***
## category_code_LT01_6_count   0.52988    0.15522   3.414 0.000694 ***
## category_code_LT01_15_count  0.37229    0.76644   0.486 0.627369    
## category_code_LT01_16_count  0.54283    1.20384   0.451 0.652252    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 492 degrees of freedom
## Multiple R-squared:  0.6079, Adjusted R-squared:  0.604 
## F-statistic: 152.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 0.611523187718746 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0553 -0.7933 -0.0063  0.9593  3.8076 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.99337    0.08852 112.890  < 2e-16 ***
## category_code_LT01_2_count  0.87530    0.07051  12.415  < 2e-16 ***
## category_code_LT01_5_count  0.97677    0.06271  15.575  < 2e-16 ***
## category_code_LT01_7_count  0.63067    0.15299   4.122  4.4e-05 ***
## category_code_LT01_8_count -0.13253    0.27809  -0.477   0.6339    
## category_code_LT01_9_count  0.39956    0.22956   1.741   0.0824 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6154, Adjusted R-squared:  0.6115 
## F-statistic: 157.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 0.610066268849167 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0381 -0.7912  0.0031  0.9267  3.8298 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97113    0.09203 108.347  < 2e-16 ***
## category_code_LT01_2_count   0.88907    0.06997  12.707  < 2e-16 ***
## category_code_LT01_5_count   0.98411    0.06265  15.708  < 2e-16 ***
## category_code_LT01_7_count   0.64511    0.15296   4.218 2.94e-05 ***
## category_code_LT01_8_count  -0.12333    0.27853  -0.443    0.658    
## category_code_LT01_10_count  0.12414    0.11428   1.086    0.278    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.614,  Adjusted R-squared:  0.6101 
## F-statistic: 156.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 0.618026915985271 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0595 -0.7507  0.0137  0.9213  3.7976 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00332    0.08775 113.993  < 2e-16 ***
## category_code_LT01_2_count   0.72291    0.08635   8.372 5.94e-16 ***
## category_code_LT01_5_count   0.96853    0.06220  15.572  < 2e-16 ***
## category_code_LT01_7_count   0.50377    0.15768   3.195 0.001489 ** 
## category_code_LT01_8_count  -0.09649    0.27567  -0.350 0.726486    
## category_code_LT01_11_count  0.39613    0.11703   3.385 0.000769 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.618 
## F-statistic: 161.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 0.609495199102157 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0621 -0.7869 -0.0263  0.9379  3.8036 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99738    0.08872 112.686  < 2e-16 ***
## category_code_LT01_2_count   0.88932    0.07151  12.436  < 2e-16 ***
## category_code_LT01_5_count   0.98086    0.06301  15.566  < 2e-16 ***
## category_code_LT01_7_count   0.65797    0.15249   4.315 1.93e-05 ***
## category_code_LT01_8_count  -0.12404    0.27888  -0.445    0.657    
## category_code_LT01_12_count  0.14178    0.20931   0.677    0.499    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6134, Adjusted R-squared:  0.6095 
## F-statistic: 156.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 0.609262289710318 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0647 -0.7787 -0.0171  0.9365  3.8033 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99766    0.08874 112.657  < 2e-16 ***
## category_code_LT01_2_count   0.89920    0.06937  12.962  < 2e-16 ***
## category_code_LT01_5_count   0.98418    0.06276  15.682  < 2e-16 ***
## category_code_LT01_7_count   0.65124    0.15397   4.230 2.79e-05 ***
## category_code_LT01_8_count  -0.10974    0.27926  -0.393    0.695    
## category_code_LT01_13_count  0.10121    0.24898   0.407    0.685    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 492 degrees of freedom
## Multiple R-squared:  0.6132, Adjusted R-squared:  0.6093 
## F-statistic:   156 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 0.609556819410415 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0646 -0.7901 -0.0114  0.9161  3.8005 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00050    0.08877 112.652  < 2e-16 ***
## category_code_LT01_2_count   0.89390    0.06988  12.792  < 2e-16 ***
## category_code_LT01_5_count   0.97990    0.06310  15.530  < 2e-16 ***
## category_code_LT01_7_count   0.64910    0.15316   4.238 2.69e-05 ***
## category_code_LT01_8_count  -0.11959    0.27867  -0.429    0.668    
## category_code_LT01_14_count  0.24275    0.33141   0.732    0.464    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6135, Adjusted R-squared:  0.6096 
## F-statistic: 156.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 0.6095499533859 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -6.066 -0.776 -0.020  0.930  3.803 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99797    0.08871 112.707  < 2e-16 ***
## category_code_LT01_2_count   0.89331    0.07003  12.756  < 2e-16 ***
## category_code_LT01_5_count   0.98525    0.06269  15.717  < 2e-16 ***
## category_code_LT01_7_count   0.66116    0.15247   4.336 1.76e-05 ***
## category_code_LT01_8_count  -0.11950    0.27868  -0.429    0.668    
## category_code_LT01_15_count  0.55180    0.75948   0.727    0.468    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6135, Adjusted R-squared:  0.6095 
## F-statistic: 156.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 0.609168318948161 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0659 -0.7872 -0.0196  0.9360  3.8027 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99827    0.08876 112.642  < 2e-16 ***
## category_code_LT01_2_count   0.90008    0.06963  12.926  < 2e-16 ***
## category_code_LT01_5_count   0.98503    0.06272  15.705  < 2e-16 ***
## category_code_LT01_7_count   0.66063    0.15257   4.330 1.81e-05 ***
## category_code_LT01_8_count  -0.11969    0.27915  -0.429    0.668    
## category_code_LT01_16_count  0.25808    1.19140   0.217    0.829    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 492 degrees of freedom
## Multiple R-squared:  0.6131, Adjusted R-squared:  0.6092 
## F-statistic: 155.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 0.611966072832294 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0286 -0.7727  0.0237  0.9463  3.8308 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97020    0.09177 108.639  < 2e-16 ***
## category_code_LT01_2_count   0.86639    0.07121  12.167  < 2e-16 ***
## category_code_LT01_5_count   0.97171    0.06196  15.683  < 2e-16 ***
## category_code_LT01_7_count   0.61768    0.15327   4.030 6.46e-05 ***
## category_code_LT01_9_count   0.37258    0.23081   1.614    0.107    
## category_code_LT01_10_count  0.10190    0.11472   0.888    0.375    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 492 degrees of freedom
## Multiple R-squared:  0.6159, Adjusted R-squared:  0.612 
## F-statistic: 157.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 0.619854300351212 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0465 -0.7875  0.0131  0.9153  3.8031 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99790    0.08754 114.208  < 2e-16 ***
## category_code_LT01_2_count   0.70260    0.08705   8.071  5.4e-15 ***
## category_code_LT01_5_count   0.95748    0.06149  15.572  < 2e-16 ***
## category_code_LT01_7_count   0.47854    0.15783   3.032 0.002557 ** 
## category_code_LT01_9_count   0.35845    0.22724   1.577 0.115348    
## category_code_LT01_11_count  0.38785    0.11686   3.319 0.000971 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6199 
## F-statistic: 163.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 0.611673815473372 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0472 -0.7809  0.0057  0.9307  3.8096 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99139    0.08847 112.941  < 2e-16 ***
## category_code_LT01_2_count   0.86346    0.07291  11.842  < 2e-16 ***
## category_code_LT01_5_count   0.96793    0.06234  15.527  < 2e-16 ***
## category_code_LT01_7_count   0.62633    0.15290   4.096 4.91e-05 ***
## category_code_LT01_9_count   0.39461    0.22940   1.720    0.086 .  
## category_code_LT01_12_count  0.13485    0.20857   0.647    0.518    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6156, Adjusted R-squared:  0.6117 
## F-statistic: 157.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 0.611588481786643 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0495 -0.7811  0.0081  0.9544  3.8094 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99157    0.08847 112.933  < 2e-16 ***
## category_code_LT01_2_count   0.87095    0.07097  12.272  < 2e-16 ***
## category_code_LT01_5_count   0.97101    0.06203  15.654  < 2e-16 ***
## category_code_LT01_7_count   0.61593    0.15446   3.988 7.68e-05 ***
## category_code_LT01_9_count   0.40507    0.23000   1.761   0.0788 .  
## category_code_LT01_13_count  0.13828    0.24841   0.557   0.5780    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6155, Adjusted R-squared:  0.6116 
## F-statistic: 157.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 0.611647068343424 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0500 -0.7838  0.0126  0.9269  3.8067 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99422    0.08853 112.885  < 2e-16 ***
## category_code_LT01_2_count   0.86919    0.07123  12.203  < 2e-16 ***
## category_code_LT01_5_count   0.96791    0.06238  15.516  < 2e-16 ***
## category_code_LT01_7_count   0.61969    0.15348   4.037 6.27e-05 ***
## category_code_LT01_9_count   0.38691    0.22986   1.683    0.093 .  
## category_code_LT01_14_count  0.20524    0.33115   0.620    0.536    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6156, Adjusted R-squared:  0.6116 
## F-statistic: 157.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 0.611787490564105 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0507 -0.7815  0.0002  0.9275  3.8090 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99194    0.08845 112.971  < 2e-16 ***
## category_code_LT01_2_count   0.86629    0.07154  12.109  < 2e-16 ***
## category_code_LT01_5_count   0.97216    0.06197  15.687  < 2e-16 ***
## category_code_LT01_7_count   0.62925    0.15285   4.117 4.51e-05 ***
## category_code_LT01_9_count   0.39867    0.22938   1.738   0.0828 .  
## category_code_LT01_15_count  0.56785    0.75732   0.750   0.4537    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 492 degrees of freedom
## Multiple R-squared:  0.6157, Adjusted R-squared:  0.6118 
## F-statistic: 157.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 0.611360123221235 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0509 -0.7834  0.0036  0.9535  3.8088 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99219    0.08850 112.900  < 2e-16 ***
## category_code_LT01_2_count   0.87425    0.07106  12.303  < 2e-16 ***
## category_code_LT01_5_count   0.97211    0.06201  15.676  < 2e-16 ***
## category_code_LT01_7_count   0.62871    0.15298   4.110 4.64e-05 ***
## category_code_LT01_9_count   0.39497    0.22958   1.720    0.086 .  
## category_code_LT01_16_count  0.17026    1.18705   0.143    0.886    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6114 
## F-statistic: 157.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 0.618684858386227 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0313 -0.7677  0.0215  0.9316  3.8228 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97811    0.09101 109.641  < 2e-16 ***
## category_code_LT01_2_count   0.71239    0.08687   8.200  2.1e-15 ***
## category_code_LT01_5_count   0.96411    0.06140  15.703  < 2e-16 ***
## category_code_LT01_7_count   0.48944    0.15787   3.100 0.002044 ** 
## category_code_LT01_10_count  0.11142    0.11303   0.986 0.324757    
## category_code_LT01_11_count  0.39350    0.11695   3.365 0.000826 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 492 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6187 
## F-statistic: 162.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 0.610212648291937 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0313 -0.7783  0.0064  0.9276  3.8309 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97009    0.09198 108.393  < 2e-16 ***
## category_code_LT01_2_count   0.87784    0.07232  12.139  < 2e-16 ***
## category_code_LT01_5_count   0.97570    0.06226  15.672  < 2e-16 ***
## category_code_LT01_7_count   0.64116    0.15285   4.195 3.24e-05 ***
## category_code_LT01_10_count  0.12011    0.11433   1.051    0.294    
## category_code_LT01_12_count  0.12907    0.20913   0.617    0.537    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.6102 
## F-statistic: 156.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 0.610042823278471 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0336 -0.7915  0.0142  0.9297  3.8309 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97005    0.09200 108.369  < 2e-16 ***
## category_code_LT01_2_count   0.88638    0.07030  12.608  < 2e-16 ***
## category_code_LT01_5_count   0.97908    0.06194  15.808  < 2e-16 ***
## category_code_LT01_7_count   0.63432    0.15422   4.113 4.58e-05 ***
## category_code_LT01_10_count  0.12199    0.11428   1.067    0.286    
## category_code_LT01_13_count  0.10132    0.24833   0.408    0.683    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.614,  Adjusted R-squared:   0.61 
## F-statistic: 156.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 0.610117639365146 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0361 -0.7803  0.0132  0.9228  3.8264 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97458    0.09241 107.933  < 2e-16 ***
## category_code_LT01_2_count   0.88464    0.07052  12.545  < 2e-16 ***
## category_code_LT01_5_count   0.97613    0.06233  15.662  < 2e-16 ***
## category_code_LT01_7_count   0.63647    0.15333   4.151  3.9e-05 ***
## category_code_LT01_10_count  0.11040    0.11688   0.945    0.345    
## category_code_LT01_14_count  0.17305    0.33878   0.511    0.610    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.614,  Adjusted R-squared:  0.6101 
## F-statistic: 156.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 0.610227554514845 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0354 -0.7695  0.0015  0.9288  3.8296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97137    0.09200 108.382  < 2e-16 ***
## category_code_LT01_2_count   0.88214    0.07083  12.455  < 2e-16 ***
## category_code_LT01_5_count   0.97987    0.06189  15.832  < 2e-16 ***
## category_code_LT01_7_count   0.64449    0.15285   4.216 2.95e-05 ***
## category_code_LT01_10_count  0.11688    0.11464   1.020    0.308    
## category_code_LT01_15_count  0.48143    0.76148   0.632    0.528    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.6102 
## F-statistic: 156.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 0.609929829167977 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0343 -0.7894  0.0042  0.9283  3.8306 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97040    0.09204 108.329  < 2e-16 ***
## category_code_LT01_2_count   0.88780    0.07053  12.587  < 2e-16 ***
## category_code_LT01_5_count   0.97966    0.06193  15.819  < 2e-16 ***
## category_code_LT01_7_count   0.64326    0.15293   4.206 3.09e-05 ***
## category_code_LT01_10_count  0.12235    0.11435   1.070    0.285    
## category_code_LT01_16_count  0.18387    1.18954   0.155    0.877    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6139, Adjusted R-squared:  0.6099 
## F-statistic: 156.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 0.617966580492867 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0573 -0.7618  0.0159  0.9198  3.7983 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00262    0.08773 114.022  < 2e-16 ***
## category_code_LT01_2_count   0.72358    0.08651   8.364 6.27e-16 ***
## category_code_LT01_5_count   0.96634    0.06171  15.661  < 2e-16 ***
## category_code_LT01_7_count   0.49947    0.15782   3.165 0.001648 ** 
## category_code_LT01_11_count  0.40360    0.12108   3.333 0.000922 ***
## category_code_LT01_12_count -0.04530    0.21406  -0.212 0.832496    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.618 
## F-statistic: 161.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 0.618002711774331 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0556 -0.7848  0.0176  0.9169  3.7988 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00211    0.08771 114.034  < 2e-16 ***
## category_code_LT01_2_count   0.72100    0.08649   8.337 7.71e-16 ***
## category_code_LT01_5_count   0.96464    0.06147  15.694  < 2e-16 ***
## category_code_LT01_7_count   0.49575    0.15865   3.125 0.001885 ** 
## category_code_LT01_11_count  0.39562    0.11709   3.379 0.000786 ***
## category_code_LT01_13_count  0.07431    0.24592   0.302 0.762633    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.618 
## F-statistic: 161.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 0.618243632281981 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0551 -0.7698  0.0127  0.9137  3.7965 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00441    0.08774 114.018  < 2e-16 ***
## category_code_LT01_2_count   0.71648    0.08684   8.251 1.45e-15 ***
## category_code_LT01_5_count   0.96062    0.06184  15.535  < 2e-16 ***
## category_code_LT01_7_count   0.49302    0.15805   3.119 0.001918 ** 
## category_code_LT01_11_count  0.39481    0.11702   3.374 0.000799 ***
## category_code_LT01_14_count  0.20781    0.32781   0.634 0.526419    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6182 
## F-statistic:   162 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 0.6180979105015 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0562 -0.7628 -0.0024  0.9214  3.7987 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00223    0.08770 114.052  < 2e-16 ***
## category_code_LT01_2_count   0.71888    0.08669   8.293 1.07e-15 ***
## category_code_LT01_5_count   0.96530    0.06144  15.712  < 2e-16 ***
## category_code_LT01_7_count   0.50388    0.15761   3.197  0.00148 ** 
## category_code_LT01_11_count  0.39274    0.11735   3.347  0.00088 ***
## category_code_LT01_15_count  0.34851    0.75339   0.463  0.64387    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6181 
## F-statistic: 161.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 0.617976382335287 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0563 -0.7629  0.0169  0.9216  3.7984 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00260    0.08772 114.028  < 2e-16 ***
## category_code_LT01_2_count   0.72014    0.08690   8.286 1.12e-15 ***
## category_code_LT01_5_count   0.96485    0.06146  15.700  < 2e-16 ***
## category_code_LT01_7_count   0.50206    0.15757   3.186  0.00153 ** 
## category_code_LT01_11_count  0.39737    0.11701   3.396  0.00074 ***
## category_code_LT01_16_count  0.28187    1.17645   0.240  0.81075    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.618 
## F-statistic: 161.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 0.609473082049289 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0572 -0.7854 -0.0163  0.9190  3.8051 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99585    0.08868 112.724  < 2e-16 ***
## category_code_LT01_2_count   0.88693    0.07181  12.351  < 2e-16 ***
## category_code_LT01_5_count   0.97598    0.06233  15.658  < 2e-16 ***
## category_code_LT01_7_count   0.64690    0.15378   4.207 3.08e-05 ***
## category_code_LT01_12_count  0.13561    0.20924   0.648    0.517    
## category_code_LT01_13_count  0.10247    0.24856   0.412    0.680    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6134, Adjusted R-squared:  0.6095 
## F-statistic: 156.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 0.609701147101862 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0571 -0.7880 -0.0065  0.9073  3.8025 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99844    0.08872 112.702  < 2e-16 ***
## category_code_LT01_2_count   0.88305    0.07215  12.240  < 2e-16 ***
## category_code_LT01_5_count   0.97205    0.06267  15.512  < 2e-16 ***
## category_code_LT01_7_count   0.64557    0.15304   4.218 2.93e-05 ***
## category_code_LT01_12_count  0.12692    0.20975   0.605    0.545    
## category_code_LT01_14_count  0.22480    0.33235   0.676    0.499    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6136, Adjusted R-squared:  0.6097 
## F-statistic: 156.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 0.609761464415033 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0578 -0.7843 -0.0205  0.9115  3.8049 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99604    0.08864 112.770  < 2e-16 ***
## category_code_LT01_2_count   0.88060    0.07254  12.139  < 2e-16 ***
## category_code_LT01_5_count   0.97657    0.06229  15.679  < 2e-16 ***
## category_code_LT01_7_count   0.65665    0.15234   4.310 1.97e-05 ***
## category_code_LT01_12_count  0.14037    0.20910   0.671    0.502    
## category_code_LT01_15_count  0.55467    0.75928   0.731    0.465    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6137, Adjusted R-squared:  0.6098 
## F-statistic: 156.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 0.609372408989632 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0580 -0.7859 -0.0192  0.9180  3.8046 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99633    0.08869 112.708  < 2e-16 ***
## category_code_LT01_2_count   0.88763    0.07216  12.301  < 2e-16 ***
## category_code_LT01_5_count   0.97640    0.06233  15.665  < 2e-16 ***
## category_code_LT01_7_count   0.65610    0.15244   4.304 2.03e-05 ***
## category_code_LT01_12_count  0.13894    0.20922   0.664    0.507    
## category_code_LT01_16_count  0.24702    1.18975   0.208    0.836    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 492 degrees of freedom
## Multiple R-squared:  0.6133, Adjusted R-squared:  0.6094 
## F-statistic: 156.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 0.609559642416961 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0596 -0.7885 -0.0026  0.9170  3.8020 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99895    0.08872 112.696  < 2e-16 ***
## category_code_LT01_2_count   0.89086    0.07024  12.683  < 2e-16 ***
## category_code_LT01_5_count   0.97497    0.06240  15.625  < 2e-16 ***
## category_code_LT01_7_count   0.63767    0.15446   4.128 4.29e-05 ***
## category_code_LT01_13_count  0.10764    0.24843   0.433    0.665    
## category_code_LT01_14_count  0.24107    0.33137   0.727    0.467    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6135, Adjusted R-squared:  0.6096 
## F-statistic: 156.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 0.609580499949421 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0607 -0.7694 -0.0164  0.9261  3.8045 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99642    0.08866 112.753  < 2e-16 ***
## category_code_LT01_2_count   0.88970    0.07045  12.628  < 2e-16 ***
## category_code_LT01_5_count   0.98021    0.06196  15.820  < 2e-16 ***
## category_code_LT01_7_count   0.64889    0.15375   4.221  2.9e-05 ***
## category_code_LT01_13_count  0.11733    0.24880   0.472    0.637    
## category_code_LT01_15_count  0.56686    0.76053   0.745    0.456    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6135, Adjusted R-squared:  0.6096 
## F-statistic: 156.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 0.609175480093112 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0609 -0.7696 -0.0130  0.9370  3.8042 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99673    0.08871 112.689  < 2e-16 ***
## category_code_LT01_2_count   0.89697    0.07003  12.809  < 2e-16 ***
## category_code_LT01_5_count   0.98006    0.06201  15.806  < 2e-16 ***
## category_code_LT01_7_count   0.64898    0.15384   4.218 2.93e-05 ***
## category_code_LT01_13_count  0.10924    0.24875   0.439    0.661    
## category_code_LT01_16_count  0.25289    1.19079   0.212    0.832    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 492 degrees of freedom
## Multiple R-squared:  0.6131, Adjusted R-squared:  0.6092 
## F-statistic: 155.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 0.609805264459369 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0604 -0.7887 -0.0120  0.9158  3.8018 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99912    0.08869 112.736  < 2e-16 ***
## category_code_LT01_2_count   0.88559    0.07085  12.499  < 2e-16 ***
## category_code_LT01_5_count   0.97587    0.06235  15.651  < 2e-16 ***
## category_code_LT01_7_count   0.64813    0.15302   4.236 2.72e-05 ***
## category_code_LT01_14_count  0.23568    0.33134   0.711    0.477    
## category_code_LT01_15_count  0.53561    0.75933   0.705    0.481    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6137, Adjusted R-squared:  0.6098 
## F-statistic: 156.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 0.609455257719571 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0605 -0.7891 -0.0110  0.9159  3.8014 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99954    0.08875 112.677  < 2e-16 ***
## category_code_LT01_2_count   0.89159    0.07059  12.631  < 2e-16 ***
## category_code_LT01_5_count   0.97541    0.06240  15.632  < 2e-16 ***
## category_code_LT01_7_count   0.64728    0.15309   4.228 2.81e-05 ***
## category_code_LT01_14_count  0.24517    0.33196   0.739    0.461    
## category_code_LT01_16_count  0.28236    1.19136   0.237    0.813    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 492 degrees of freedom
## Multiple R-squared:  0.6134, Adjusted R-squared:  0.6095 
## F-statistic: 156.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609443423174882 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0617 -0.7660 -0.0237  0.9173  3.8040 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99697    0.08868 112.732  < 2e-16 ***
## category_code_LT01_2_count   0.89119    0.07071  12.603  < 2e-16 ***
## category_code_LT01_5_count   0.98084    0.06196  15.831  < 2e-16 ***
## category_code_LT01_7_count   0.65941    0.15241   4.326 1.84e-05 ***
## category_code_LT01_15_count  0.55362    0.76007   0.728    0.467    
## category_code_LT01_16_count  0.26519    1.19030   0.223    0.824    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 492 degrees of freedom
## Multiple R-squared:  0.6134, Adjusted R-squared:  0.6094 
## F-statistic: 156.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 0.612813403944354 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0603 -0.7909  0.0229  0.9003  4.3310 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00133    0.08839 113.151  < 2e-16 ***
## category_code_LT01_2_count   0.73631    0.08716   8.448 3.37e-16 ***
## category_code_LT01_5_count   0.97251    0.06268  15.516  < 2e-16 ***
## category_code_LT01_8_count  -0.07814    0.27749  -0.282    0.778    
## category_code_LT01_9_count   0.42416    0.22853   1.856    0.064 .  
## category_code_LT01_11_count  0.48866    0.11303   4.323 1.86e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6167, Adjusted R-squared:  0.6128 
## F-statistic: 158.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 0.611281991924444 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0407 -0.7644  0.0121  0.9043  4.3315 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97631    0.09191 108.542  < 2e-16 ***
## category_code_LT01_2_count   0.74812    0.08697   8.602  < 2e-16 ***
## category_code_LT01_5_count   0.98027    0.06262  15.655  < 2e-16 ***
## category_code_LT01_8_count  -0.06755    0.27793  -0.243    0.808    
## category_code_LT01_10_count  0.13909    0.11383   1.222    0.222    
## category_code_LT01_11_count  0.49779    0.11307   4.403 1.31e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6152, Adjusted R-squared:  0.6113 
## F-statistic: 157.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 0.610218721773077 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0737 -0.7740  0.0029  0.8902  4.2687 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00703    0.08865 112.883  < 2e-16 ***
## category_code_LT01_2_count   0.76353    0.08647   8.830  < 2e-16 ***
## category_code_LT01_5_count   0.98359    0.06289  15.640  < 2e-16 ***
## category_code_LT01_8_count  -0.05400    0.27848  -0.194    0.846    
## category_code_LT01_11_count  0.51674    0.11682   4.423  1.2e-05 ***
## category_code_LT01_12_count -0.08281    0.21606  -0.383    0.702    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.6102 
## F-statistic: 156.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 0.610445873038037 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0700 -0.7785  0.0111  0.8937  4.2823 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00591    0.08862 112.908  < 2e-16 ***
## category_code_LT01_2_count   0.75755    0.08658   8.750  < 2e-16 ***
## category_code_LT01_5_count   0.97985    0.06273  15.619  < 2e-16 ***
## category_code_LT01_8_count  -0.04875    0.27854  -0.175    0.861    
## category_code_LT01_11_count  0.49975    0.11335   4.409 1.28e-05 ***
## category_code_LT01_13_count  0.16267    0.24697   0.659    0.510    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6104 
## F-statistic: 156.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 0.610734089923604 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0702 -0.7652  0.0030  0.8916  4.2894 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00948    0.08864 112.919  < 2e-16 ***
## category_code_LT01_2_count   0.75240    0.08694   8.654  < 2e-16 ***
## category_code_LT01_5_count   0.97508    0.06308  15.457  < 2e-16 ***
## category_code_LT01_8_count  -0.06335    0.27808  -0.228    0.820    
## category_code_LT01_11_count  0.49973    0.11316   4.416 1.24e-05 ***
## category_code_LT01_14_count  0.29480    0.32991   0.894    0.372    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6147, Adjusted R-squared:  0.6107 
## F-statistic:   157 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 0.610201490301193 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0720 -0.7812 -0.0008  0.8908  4.2782 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00651    0.08864 112.886  < 2e-16 ***
## category_code_LT01_2_count   0.75920    0.08668   8.759  < 2e-16 ***
## category_code_LT01_5_count   0.98190    0.06270  15.661  < 2e-16 ***
## category_code_LT01_8_count  -0.06012    0.27825  -0.216    0.829    
## category_code_LT01_11_count  0.50256    0.11335   4.434 1.14e-05 ***
## category_code_LT01_15_count  0.26911    0.76078   0.354    0.724    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.6102 
## F-statistic: 156.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 0.610131930223064 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0720 -0.7730  0.0012  0.8958  4.2763 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00681    0.08866 112.866  < 2e-16 ***
## category_code_LT01_2_count   0.75997    0.08690   8.745  < 2e-16 ***
## category_code_LT01_5_count   0.98154    0.06270  15.654  < 2e-16 ***
## category_code_LT01_8_count  -0.06137    0.27860  -0.220    0.826    
## category_code_LT01_11_count  0.50584    0.11308   4.473 9.57e-06 ***
## category_code_LT01_16_count  0.22984    1.18978   0.193    0.847    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.6101 
## F-statistic: 156.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.613547135717567 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0323 -0.7702  0.0257  0.9183  4.3775 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97580    0.09161 108.888  < 2e-16 ***
## category_code_LT01_2_count   0.72625    0.08760   8.290 1.09e-15 ***
## category_code_LT01_5_count   0.96899    0.06186  15.663  < 2e-16 ***
## category_code_LT01_9_count   0.39421    0.22978   1.716   0.0869 .  
## category_code_LT01_10_count  0.11504    0.11427   1.007   0.3145    
## category_code_LT01_11_count  0.48384    0.11304   4.280 2.24e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 492 degrees of freedom
## Multiple R-squared:  0.6174, Adjusted R-squared:  0.6135 
## F-statistic: 158.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 0.600089240446329 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0360 -0.8048 -0.0094  1.0031  3.9021 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96428    0.09316 106.964   <2e-16 ***
## category_code_LT01_2_count   0.96038    0.06813  14.096   <2e-16 ***
## category_code_LT01_5_count   0.99084    0.06272  15.797   <2e-16 ***
## category_code_LT01_9_count   0.48146    0.23353   2.062   0.0398 *  
## category_code_LT01_10_count  0.13240    0.11621   1.139   0.2552    
## category_code_LT01_13_count  0.26749    0.24971   1.071   0.2846    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.424 on 492 degrees of freedom
## Multiple R-squared:  0.6041, Adjusted R-squared:  0.6001 
## F-statistic: 150.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.612862593420966 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0596 -0.7906  0.0148  0.9017  4.3284 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00107    0.08835 113.199  < 2e-16 ***
## category_code_LT01_2_count   0.73771    0.08727   8.453 3.24e-16 ***
## category_code_LT01_5_count   0.97184    0.06215  15.636  < 2e-16 ***
## category_code_LT01_9_count   0.42094    0.22836   1.843   0.0659 .  
## category_code_LT01_11_count  0.50011    0.11677   4.283 2.22e-05 ***
## category_code_LT01_12_count -0.08102    0.21513  -0.377   0.7066    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6168, Adjusted R-squared:  0.6129 
## F-statistic: 158.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.61323779773905 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0555 -0.7893  0.0229  0.9148  4.3451 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99976    0.08830 113.246  < 2e-16 ***
## category_code_LT01_2_count   0.73028    0.08740   8.355 6.72e-16 ***
## category_code_LT01_5_count   0.96777    0.06194  15.625  < 2e-16 ***
## category_code_LT01_9_count   0.43282    0.22867   1.893    0.059 .  
## category_code_LT01_11_count  0.48178    0.11334   4.251 2.55e-05 ***
## category_code_LT01_13_count  0.19373    0.24619   0.787    0.432    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6171, Adjusted R-squared:  0.6132 
## F-statistic: 158.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.613212177334364 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0564 -0.7927  0.0253  0.9056  4.3452 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00317    0.08837 113.203  < 2e-16 ***
## category_code_LT01_2_count   0.72861    0.08764   8.314 9.11e-16 ***
## category_code_LT01_5_count   0.96427    0.06230  15.477  < 2e-16 ***
## category_code_LT01_9_count   0.40957    0.22880   1.790   0.0741 .  
## category_code_LT01_11_count  0.48465    0.11311   4.285 2.20e-05 ***
## category_code_LT01_14_count  0.25244    0.32960   0.766   0.4441    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6171, Adjusted R-squared:  0.6132 
## F-statistic: 158.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.61287312837482 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0576 -0.7900  0.0057  0.9023  4.3389 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00045    0.08834 113.208  < 2e-16 ***
## category_code_LT01_2_count   0.73291    0.08749   8.377 5.70e-16 ***
## category_code_LT01_5_count   0.96992    0.06191  15.666  < 2e-16 ***
## category_code_LT01_9_count   0.42378    0.22841   1.855   0.0641 .  
## category_code_LT01_11_count  0.48577    0.11332   4.287 2.18e-05 ***
## category_code_LT01_15_count  0.29874    0.75828   0.394   0.6938    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6168, Adjusted R-squared:  0.6129 
## F-statistic: 158.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.612764142685258 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0577 -0.7903  0.0188  0.9068  4.3348 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00070    0.08836 113.183  < 2e-16 ***
## category_code_LT01_2_count   0.73477    0.08765   8.383 5.46e-16 ***
## category_code_LT01_5_count   0.96964    0.06193  15.657  < 2e-16 ***
## category_code_LT01_9_count   0.42087    0.22848   1.842   0.0661 .  
## category_code_LT01_11_count  0.48936    0.11306   4.328 1.82e-05 ***
## category_code_LT01_16_count  0.15309    1.18478   0.129   0.8972    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 492 degrees of freedom
## Multiple R-squared:  0.6167, Adjusted R-squared:  0.6128 
## F-statistic: 158.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.611380852524642 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0403 -0.7656  0.0183  0.8863  4.3288 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97604    0.09187 108.584  < 2e-16 ***
## category_code_LT01_2_count   0.74956    0.08704   8.611  < 2e-16 ***
## category_code_LT01_5_count   0.98018    0.06205  15.795  < 2e-16 ***
## category_code_LT01_10_count  0.13982    0.11382   1.228    0.220    
## category_code_LT01_11_count  0.51061    0.11675   4.374 1.49e-05 ***
## category_code_LT01_12_count -0.09255    0.21563  -0.429    0.668    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6114 
## F-statistic: 157.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.61155301854773 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0374 -0.7653  0.0288  0.8994  4.3408 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97571    0.09185 108.607  < 2e-16 ***
## category_code_LT01_2_count   0.74393    0.08713   8.538  < 2e-16 ***
## category_code_LT01_5_count   0.97648    0.06184  15.789  < 2e-16 ***
## category_code_LT01_10_count  0.13623    0.11380   1.197    0.232    
## category_code_LT01_11_count  0.49269    0.11334   4.347 1.68e-05 ***
## category_code_LT01_13_count  0.15628    0.24636   0.634    0.526    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6155, Adjusted R-squared:  0.6116 
## F-statistic: 157.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.611561918062364 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0408 -0.7710  0.0303  0.9016  4.3383 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98140    0.09227 108.177  < 2e-16 ***
## category_code_LT01_2_count   0.74241    0.08732   8.502 2.24e-16 ***
## category_code_LT01_5_count   0.97309    0.06225  15.632  < 2e-16 ***
## category_code_LT01_10_count  0.12221    0.11649   1.049    0.295    
## category_code_LT01_11_count  0.49478    0.11314   4.373 1.50e-05 ***
## category_code_LT01_14_count  0.21704    0.33745   0.643    0.520    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6155, Adjusted R-squared:  0.6116 
## F-statistic: 157.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.611286741191473 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0390 -0.7658  0.0168  0.8955  4.3358 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97622    0.09190 108.554  < 2e-16 ***
## category_code_LT01_2_count   0.74609    0.08720   8.556  < 2e-16 ***
## category_code_LT01_5_count   0.97801    0.06183  15.818  < 2e-16 ***
## category_code_LT01_10_count  0.13605    0.11415   1.192    0.234    
## category_code_LT01_11_count  0.49613    0.11332   4.378 1.46e-05 ***
## category_code_LT01_15_count  0.19440    0.76206   0.255    0.799    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6152, Adjusted R-squared:  0.6113 
## F-statistic: 157.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.611250383606305 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0386 -0.7656  0.0182  0.8947  4.3351 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97605    0.09191 108.540  < 2e-16 ***
## category_code_LT01_2_count   0.74649    0.08745   8.536  < 2e-16 ***
## category_code_LT01_5_count   0.97771    0.06184  15.810  < 2e-16 ***
## category_code_LT01_10_count  0.13779    0.11387   1.210    0.227    
## category_code_LT01_11_count  0.49841    0.11309   4.407 1.29e-05 ***
## category_code_LT01_16_count  0.16391    1.18739   0.138    0.890    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 492 degrees of freedom
## Multiple R-squared:  0.6152, Adjusted R-squared:  0.6113 
## F-statistic: 157.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.610548690591714 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0703 -0.7692 -0.0031  0.8977  4.2793 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00594    0.08857 112.974  < 2e-16 ***
## category_code_LT01_2_count   0.75896    0.08665   8.759  < 2e-16 ***
## category_code_LT01_5_count   0.98026    0.06215  15.773  < 2e-16 ***
## category_code_LT01_11_count  0.51157    0.11705   4.371 1.51e-05 ***
## category_code_LT01_12_count -0.08645    0.21578  -0.401    0.689    
## category_code_LT01_13_count  0.16624    0.24659   0.674    0.501    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6105 
## F-statistic: 156.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.610856379709229 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0703 -0.7774 -0.0015  0.8885  4.2865 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00954    0.08859 112.984  < 2e-16 ***
## category_code_LT01_2_count   0.75377    0.08700   8.664  < 2e-16 ***
## category_code_LT01_5_count   0.97509    0.06250  15.601  < 2e-16 ***
## category_code_LT01_11_count  0.51317    0.11679   4.394 1.36e-05 ***
## category_code_LT01_12_count -0.09825    0.21618  -0.454    0.650    
## category_code_LT01_14_count  0.30368    0.33058   0.919    0.359    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6148, Adjusted R-squared:  0.6109 
## F-statistic:   157 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.610279105713581 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0718 -0.7695 -0.0152  0.8909  4.2753 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00641    0.08860 112.945  < 2e-16 ***
## category_code_LT01_2_count   0.76066    0.08679   8.765  < 2e-16 ***
## category_code_LT01_5_count   0.98181    0.06213  15.802  < 2e-16 ***
## category_code_LT01_11_count  0.51410    0.11715   4.388  1.4e-05 ***
## category_code_LT01_12_count -0.08214    0.21596  -0.380    0.704    
## category_code_LT01_15_count  0.25678    0.76107   0.337    0.736    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6103 
## F-statistic: 156.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.610213595166886 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0719 -0.7689 -0.0063  0.8909  4.2733 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00668    0.08861 112.928  < 2e-16 ***
## category_code_LT01_2_count   0.76150    0.08701   8.752  < 2e-16 ***
## category_code_LT01_5_count   0.98148    0.06215  15.793  < 2e-16 ***
## category_code_LT01_11_count  0.51748    0.11681   4.430 1.16e-05 ***
## category_code_LT01_12_count -0.08406    0.21588  -0.389    0.697    
## category_code_LT01_16_count  0.20966    1.18831   0.176    0.860    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.6102 
## F-statistic: 156.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.611041965000081 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0665 -0.7791  0.0157  0.8933  4.3001 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00825    0.08856 113.010  < 2e-16 ***
## category_code_LT01_2_count   0.74785    0.08712   8.584  < 2e-16 ***
## category_code_LT01_5_count   0.97140    0.06233  15.585  < 2e-16 ***
## category_code_LT01_11_count  0.49424    0.11344   4.357 1.61e-05 ***
## category_code_LT01_13_count  0.16371    0.24642   0.664    0.507    
## category_code_LT01_14_count  0.29208    0.32973   0.886    0.376    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.615,  Adjusted R-squared:  0.611 
## F-statistic: 157.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.610543848557855 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0682 -0.7807  0.0015  0.8914  4.2901 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00531    0.08856 112.980  < 2e-16 ***
## category_code_LT01_2_count   0.75409    0.08690   8.678  < 2e-16 ***
## category_code_LT01_5_count   0.97822    0.06191  15.800  < 2e-16 ***
## category_code_LT01_11_count  0.49643    0.11367   4.367 1.53e-05 ***
## category_code_LT01_13_count  0.17102    0.24705   0.692    0.489    
## category_code_LT01_15_count  0.29936    0.76183   0.393    0.695    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6105 
## F-statistic: 156.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.61045662542751 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0683 -0.7762  0.0056  0.8964  4.2877 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00563    0.08858 112.961  < 2e-16 ***
## category_code_LT01_2_count   0.75509    0.08712   8.667  < 2e-16 ***
## category_code_LT01_5_count   0.97782    0.06193  15.789  < 2e-16 ***
## category_code_LT01_11_count  0.50021    0.11336   4.413 1.26e-05 ***
## category_code_LT01_13_count  0.16715    0.24681   0.677    0.499    
## category_code_LT01_16_count  0.24995    1.18881   0.210    0.834    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6105 
## F-statistic: 156.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.610782630980548 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0681 -0.7597  0.0037  0.8874  4.2960 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00873    0.08859 112.983  < 2e-16 ***
## category_code_LT01_2_count   0.74960    0.08723   8.594  < 2e-16 ***
## category_code_LT01_5_count   0.97305    0.06231  15.615  < 2e-16 ***
## category_code_LT01_11_count  0.49729    0.11343   4.384 1.42e-05 ***
## category_code_LT01_14_count  0.29159    0.32988   0.884    0.377    
## category_code_LT01_15_count  0.25586    0.76023   0.337    0.737    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6147, Adjusted R-squared:  0.6108 
## F-statistic:   157 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.610736584605665 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0681 -0.7595  0.0085  0.8892  4.2955 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00913    0.08860 112.967  < 2e-16 ***
## category_code_LT01_2_count   0.74963    0.08754   8.563  < 2e-16 ***
## category_code_LT01_5_count   0.97247    0.06234  15.600  < 2e-16 ***
## category_code_LT01_11_count  0.50040    0.11316   4.422  1.2e-05 ***
## category_code_LT01_14_count  0.29789    0.33041   0.902    0.368    
## category_code_LT01_16_count  0.27908    1.18938   0.235    0.815    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6147, Adjusted R-squared:  0.6107 
## F-statistic:   157 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.610194773495332 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0699 -0.7784 -0.0018  0.8903  4.2834 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00611    0.08860 112.933  < 2e-16 ***
## category_code_LT01_2_count   0.75689    0.08724   8.676  < 2e-16 ***
## category_code_LT01_5_count   0.97952    0.06191  15.821  < 2e-16 ***
## category_code_LT01_11_count  0.50316    0.11336   4.439 1.12e-05 ***
## category_code_LT01_15_count  0.27219    0.76122   0.358    0.721    
## category_code_LT01_16_count  0.23238    1.18900   0.195    0.845    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.6102 
## F-statistic: 156.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 0.631630320481935 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9792 -0.7364  0.0115  0.9312  3.4791 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97442    0.08624 115.662  < 2e-16 ***
## category_code_LT01_3_count  0.32838    0.11166   2.941  0.00343 ** 
## category_code_LT01_4_count  0.74294    0.09004   8.251 1.45e-15 ***
## category_code_LT01_5_count  0.89428    0.06153  14.534  < 2e-16 ***
## category_code_LT01_6_count  0.44774    0.14881   3.009  0.00276 ** 
## category_code_LT01_7_count  0.49249    0.15168   3.247  0.00125 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 492 degrees of freedom
## Multiple R-squared:  0.6353, Adjusted R-squared:  0.6316 
## F-statistic: 171.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 0.62406687306559 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9927 -0.7514  0.0121  0.9037  3.4573 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97633    0.08715 114.471  < 2e-16 ***
## category_code_LT01_3_count  0.34915    0.11266   3.099  0.00205 ** 
## category_code_LT01_4_count  0.84058    0.08572   9.806  < 2e-16 ***
## category_code_LT01_5_count  0.91111    0.06272  14.526  < 2e-16 ***
## category_code_LT01_6_count  0.45780    0.15042   3.043  0.00246 ** 
## category_code_LT01_8_count -0.17972    0.27355  -0.657  0.51149    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 492 degrees of freedom
## Multiple R-squared:  0.6278, Adjusted R-squared:  0.6241 
## F-statistic:   166 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 0.626063628257118 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9782 -0.7556  0.0284  0.9223  3.5021 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97077    0.08692 114.717  < 2e-16 ***
## category_code_LT01_3_count  0.31759    0.11367   2.794  0.00541 ** 
## category_code_LT01_4_count  0.82662    0.08587   9.626  < 2e-16 ***
## category_code_LT01_5_count  0.89817    0.06203  14.480  < 2e-16 ***
## category_code_LT01_6_count  0.43960    0.15015   2.928  0.00357 ** 
## category_code_LT01_9_count  0.39465    0.22556   1.750  0.08081 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6261 
## F-statistic: 167.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 0.623939298505299 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9752 -0.7465 -0.0150  0.9220  3.4122 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96267    0.09024 110.400  < 2e-16 ***
## category_code_LT01_3_count   0.33790    0.11432   2.956  0.00327 ** 
## category_code_LT01_4_count   0.84050    0.08574   9.803  < 2e-16 ***
## category_code_LT01_5_count   0.90556    0.06208  14.587  < 2e-16 ***
## category_code_LT01_6_count   0.44232    0.15209   2.908  0.00380 ** 
## category_code_LT01_10_count  0.05901    0.11471   0.514  0.60721    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 492 degrees of freedom
## Multiple R-squared:  0.6277, Adjusted R-squared:  0.6239 
## F-statistic: 165.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 0.630779471648376 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9922 -0.7432  0.0268  0.9123  3.4616 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98212    0.08637 115.573  < 2e-16 ***
## category_code_LT01_3_count   0.26067    0.11520   2.263  0.02409 *  
## category_code_LT01_4_count   0.70944    0.09515   7.456 4.05e-13 ***
## category_code_LT01_5_count   0.90193    0.06152  14.661  < 2e-16 ***
## category_code_LT01_6_count   0.37702    0.15108   2.495  0.01290 *  
## category_code_LT01_11_count  0.34883    0.11387   3.063  0.00231 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 492 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:  0.6308 
## F-statistic: 170.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 0.623833827240932 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9856 -0.7522  0.0096  0.9193  3.4675 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97454    0.08715 114.456  < 2e-16 ***
## category_code_LT01_3_count   0.34503    0.11296   3.055  0.00238 ** 
## category_code_LT01_4_count   0.83698    0.08639   9.689  < 2e-16 ***
## category_code_LT01_5_count   0.90338    0.06229  14.503  < 2e-16 ***
## category_code_LT01_6_count   0.44762    0.15148   2.955  0.00328 ** 
## category_code_LT01_12_count  0.07330    0.20602   0.356  0.72216    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 492 degrees of freedom
## Multiple R-squared:  0.6276, Adjusted R-squared:  0.6238 
## F-statistic: 165.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 0.623967754200153 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9861 -0.7497  0.0106  0.9140  3.4666 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97447    0.08713 114.476  < 2e-16 ***
## category_code_LT01_3_count   0.34655    0.11268   3.075  0.00222 ** 
## category_code_LT01_4_count   0.83418    0.08655   9.638  < 2e-16 ***
## category_code_LT01_5_count   0.90426    0.06210  14.562  < 2e-16 ***
## category_code_LT01_6_count   0.45510    0.15035   3.027  0.00260 ** 
## category_code_LT01_13_count  0.13327    0.24257   0.549  0.58297    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 492 degrees of freedom
## Multiple R-squared:  0.6278, Adjusted R-squared:  0.624 
## F-statistic: 165.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 0.624273682069829 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9853 -0.7420 -0.0024  0.9244  3.4696 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97718    0.08714 114.493  < 2e-16 ***
## category_code_LT01_3_count   0.35068    0.11266   3.113  0.00196 ** 
## category_code_LT01_4_count   0.82308    0.08824   9.328  < 2e-16 ***
## category_code_LT01_5_count   0.89913    0.06246  14.394  < 2e-16 ***
## category_code_LT01_6_count   0.46462    0.15079   3.081  0.00218 ** 
## category_code_LT01_14_count  0.27469    0.32768   0.838  0.40229    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 492 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6243 
## F-statistic: 166.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 0.623750542947682 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9868 -0.7542  0.0052  0.9228  3.4657 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97464    0.08716 114.442  < 2e-16 ***
## category_code_LT01_3_count   0.34978    0.11359   3.079  0.00219 ** 
## category_code_LT01_4_count   0.84135    0.08590   9.795  < 2e-16 ***
## category_code_LT01_5_count   0.90492    0.06212  14.568  < 2e-16 ***
## category_code_LT01_6_count   0.45494    0.15050   3.023  0.00263 ** 
## category_code_LT01_15_count -0.10012    0.75376  -0.133  0.89439    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 492 degrees of freedom
## Multiple R-squared:  0.6275, Adjusted R-squared:  0.6238 
## F-statistic: 165.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 0.624354197803983 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9862 -0.7460  0.0018  0.9178  3.4681 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97494    0.08709 114.542  < 2e-16 ***
## category_code_LT01_3_count   0.33419    0.11362   2.941  0.00342 ** 
## category_code_LT01_4_count   0.83995    0.08569   9.802  < 2e-16 ***
## category_code_LT01_5_count   0.90362    0.06207  14.559  < 2e-16 ***
## category_code_LT01_6_count   0.46458    0.15071   3.083  0.00217 ** 
## category_code_LT01_16_count  1.05308    1.17131   0.899  0.36906    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6244 
## F-statistic: 166.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 0.62517133206472 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0160 -0.7632  0.0384  0.8551  3.4304 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.99356    0.08683 115.090  < 2e-16 ***
## category_code_LT01_3_count  0.36942    0.11187   3.302  0.00103 ** 
## category_code_LT01_4_count  0.82873    0.08615   9.620  < 2e-16 ***
## category_code_LT01_5_count  0.91986    0.06240  14.742  < 2e-16 ***
## category_code_LT01_7_count  0.50161    0.15306   3.277  0.00112 ** 
## category_code_LT01_8_count -0.17674    0.27309  -0.647  0.51782    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6289, Adjusted R-squared:  0.6252 
## F-statistic: 166.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 0.62676842693814 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0017 -0.7390  0.0459  0.8598  3.4497 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.98776    0.08665 115.270  < 2e-16 ***
## category_code_LT01_3_count  0.34023    0.11297   3.012  0.00273 ** 
## category_code_LT01_4_count  0.81841    0.08621   9.493  < 2e-16 ***
## category_code_LT01_5_count  0.90754    0.06172  14.705  < 2e-16 ***
## category_code_LT01_7_count  0.47348    0.15348   3.085  0.00215 ** 
## category_code_LT01_9_count  0.35951    0.22620   1.589  0.11263    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 492 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.6268 
## F-statistic: 167.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 0.625239349915722 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9931 -0.7544  0.0488  0.8671  3.3669 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97468    0.09007 110.739  < 2e-16 ***
## category_code_LT01_3_count   0.35319    0.11375   3.105  0.00201 ** 
## category_code_LT01_4_count   0.82707    0.08617   9.598  < 2e-16 ***
## category_code_LT01_5_count   0.91394    0.06171  14.810  < 2e-16 ***
## category_code_LT01_7_count   0.48994    0.15345   3.193  0.00150 ** 
## category_code_LT01_10_count  0.08095    0.11355   0.713  0.47625    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6252 
## F-statistic: 166.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 0.630686919822671 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0119 -0.7818  0.0588  0.8768  3.4385 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99605    0.08617 116.010  < 2e-16 ***
## category_code_LT01_3_count   0.28522    0.11493   2.482  0.01341 *  
## category_code_LT01_4_count   0.71536    0.09469   7.555 2.06e-13 ***
## category_code_LT01_5_count   0.91028    0.06128  14.856  < 2e-16 ***
## category_code_LT01_7_count   0.38777    0.15697   2.470  0.01384 *  
## category_code_LT01_11_count  0.32361    0.11607   2.788  0.00551 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 492 degrees of freedom
## Multiple R-squared:  0.6344, Adjusted R-squared:  0.6307 
## F-statistic: 170.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 0.625200674546193 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0067 -0.7612  0.0509  0.8718  3.4438 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99099    0.08680 115.104  < 2e-16 ***
## category_code_LT01_3_count   0.36157    0.11225   3.221  0.00136 ** 
## category_code_LT01_4_count   0.81965    0.08719   9.400  < 2e-16 ***
## category_code_LT01_5_count   0.91005    0.06198  14.683  < 2e-16 ***
## category_code_LT01_7_count   0.49715    0.15300   3.249  0.00124 ** 
## category_code_LT01_12_count  0.13807    0.20415   0.676  0.49917    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6252 
## F-statistic: 166.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 0.624865129085416 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0101 -0.7632  0.0494  0.8567  3.4388 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99182    0.08683 115.074  < 2e-16 ***
## category_code_LT01_3_count   0.36777    0.11191   3.286  0.00109 ** 
## category_code_LT01_4_count   0.82774    0.08654   9.564  < 2e-16 ***
## category_code_LT01_5_count   0.91377    0.06175  14.797  < 2e-16 ***
## category_code_LT01_7_count   0.49616    0.15414   3.219  0.00137 ** 
## category_code_LT01_13_count  0.03172    0.24398   0.130  0.89663    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6249 
## F-statistic: 166.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 0.62494538807273 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0099 -0.7633  0.0475  0.8672  3.4399 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99306    0.08689 115.014  < 2e-16 ***
## category_code_LT01_3_count   0.36969    0.11199   3.301  0.00103 ** 
## category_code_LT01_4_count   0.82307    0.08770   9.385  < 2e-16 ***
## category_code_LT01_5_count   0.91169    0.06206  14.690  < 2e-16 ***
## category_code_LT01_7_count   0.49464    0.15344   3.224  0.00135 ** 
## category_code_LT01_14_count  0.11435    0.32713   0.350  0.72683    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6249 
## F-statistic: 166.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 0.624858931349179 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0104 -0.7636  0.0462  0.8614  3.4384 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99193    0.08683 115.073  < 2e-16 ***
## category_code_LT01_3_count   0.36657    0.11290   3.247  0.00125 ** 
## category_code_LT01_4_count   0.82811    0.08647   9.577  < 2e-16 ***
## category_code_LT01_5_count   0.91405    0.06176  14.800  < 2e-16 ***
## category_code_LT01_7_count   0.49901    0.15313   3.259  0.00120 ** 
## category_code_LT01_15_count  0.07046    0.75246   0.094  0.92543    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6249 
## F-statistic: 166.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 0.625200054978838 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0101 -0.7629  0.0404  0.8657  3.4391 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99232    0.08679 115.129  < 2e-16 ***
## category_code_LT01_3_count   0.35841    0.11274   3.179  0.00157 ** 
## category_code_LT01_4_count   0.82966    0.08615   9.630  < 2e-16 ***
## category_code_LT01_5_count   0.91310    0.06173  14.793  < 2e-16 ***
## category_code_LT01_7_count   0.49890    0.15298   3.261  0.00119 ** 
## category_code_LT01_16_count  0.78822    1.16653   0.676  0.49955    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6252 
## F-statistic: 166.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 0.619827451594698 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0133 -0.7781  0.0502  0.8840  3.4321 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.98903    0.08749 114.179  < 2e-16 ***
## category_code_LT01_3_count  0.35492    0.11394   3.115  0.00195 ** 
## category_code_LT01_4_count  0.91088    0.08162  11.160  < 2e-16 ***
## category_code_LT01_5_count  0.92243    0.06289  14.667  < 2e-16 ***
## category_code_LT01_8_count -0.16525    0.27503  -0.601  0.54823    
## category_code_LT01_9_count  0.43542    0.22719   1.917  0.05588 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6198 
## F-statistic: 163.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 0.617717416531526 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0001 -0.7600  0.0429  0.8660  3.3206 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97042    0.09098 109.586   <2e-16 ***
## category_code_LT01_3_count   0.36897    0.11481   3.214   0.0014 ** 
## category_code_LT01_4_count   0.92480    0.08141  11.359   <2e-16 ***
## category_code_LT01_5_count   0.93023    0.06293  14.782   <2e-16 ***
## category_code_LT01_8_count  -0.15419    0.27571  -0.559   0.5763    
## category_code_LT01_10_count  0.11070    0.11435   0.968   0.3335    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.6177 
## F-statistic: 161.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 0.626262690165262 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0225 -0.7703  0.0444  0.8745  3.4231 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99858    0.08672 115.302  < 2e-16 ***
## category_code_LT01_3_count   0.28291    0.11565   2.446 0.014779 *  
## category_code_LT01_4_count   0.76386    0.09330   8.187 2.31e-15 ***
## category_code_LT01_5_count   0.92192    0.06227  14.805  < 2e-16 ***
## category_code_LT01_8_count  -0.12381    0.27266  -0.454 0.649962    
## category_code_LT01_11_count  0.39482    0.11300   3.494 0.000519 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6263 
## F-statistic: 167.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 0.617406191824437 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0199 -0.7747  0.0420  0.8707  3.4239 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99299    0.08774 113.899  < 2e-16 ***
## category_code_LT01_3_count   0.38261    0.11326   3.378 0.000788 ***
## category_code_LT01_4_count   0.91921    0.08250  11.141  < 2e-16 ***
## category_code_LT01_5_count   0.92626    0.06320  14.657  < 2e-16 ***
## category_code_LT01_8_count  -0.15611    0.27594  -0.566 0.571845    
## category_code_LT01_12_count  0.15111    0.20637   0.732 0.464384    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6174 
## F-statistic: 161.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 0.617168184234785 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0226 -0.7832  0.0465  0.8574  3.4200 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99361    0.08776 113.879  < 2e-16 ***
## category_code_LT01_3_count   0.38845    0.11292   3.440 0.000631 ***
## category_code_LT01_4_count   0.92387    0.08217  11.244  < 2e-16 ***
## category_code_LT01_5_count   0.92927    0.06301  14.748  < 2e-16 ***
## category_code_LT01_8_count  -0.14129    0.27633  -0.511 0.609359    
## category_code_LT01_13_count  0.11755    0.24515   0.480 0.631787    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6172 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 0.617258417126852 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0230 -0.7793  0.0484  0.8549  3.4208 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99592    0.08781 113.834  < 2e-16 ***
## category_code_LT01_3_count   0.39227    0.11297   3.472 0.000561 ***
## category_code_LT01_4_count   0.91849    0.08344  11.008  < 2e-16 ***
## category_code_LT01_5_count   0.92645    0.06331  14.634  < 2e-16 ***
## category_code_LT01_8_count  -0.15151    0.27586  -0.549 0.583087    
## category_code_LT01_14_count  0.19389    0.32963   0.588 0.556669    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6173 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 0.616989317219554 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0236 -0.7834  0.0348  0.8594  3.4186 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.993889   0.087777 113.855  < 2e-16 ***
## category_code_LT01_3_count   0.389732   0.113904   3.422 0.000674 ***
## category_code_LT01_4_count   0.929531   0.081576  11.395  < 2e-16 ***
## category_code_LT01_5_count   0.930279   0.063012  14.764  < 2e-16 ***
## category_code_LT01_8_count  -0.148970   0.275933  -0.540 0.589526    
## category_code_LT01_15_count -0.005863   0.759932  -0.008 0.993847    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.617 
## F-statistic: 161.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 0.61735340605865 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0238 -0.7840  0.0346  0.8583  3.4187 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99444    0.08774 113.914  < 2e-16 ***
## category_code_LT01_3_count   0.37991    0.11375   3.340 0.000902 ***
## category_code_LT01_4_count   0.93049    0.08132  11.442  < 2e-16 ***
## category_code_LT01_5_count   0.92977    0.06297  14.766  < 2e-16 ***
## category_code_LT01_8_count  -0.15802    0.27611  -0.572 0.567370    
## category_code_LT01_16_count  0.80743    1.18002   0.684 0.494139    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6174 
## F-statistic: 161.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 0.620003115715513 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9895 -0.7586  0.0647  0.8870  3.3692 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96902    0.09068 109.931  < 2e-16 ***
## category_code_LT01_3_count   0.33880    0.11557   2.932  0.00353 ** 
## category_code_LT01_4_count   0.90757    0.08169  11.109  < 2e-16 ***
## category_code_LT01_5_count   0.91705    0.06220  14.744  < 2e-16 ***
## category_code_LT01_9_count   0.41303    0.22827   1.809  0.07099 .  
## category_code_LT01_10_count  0.08793    0.11460   0.767  0.44333    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 492 degrees of freedom
## Multiple R-squared:  0.6238, Adjusted R-squared:   0.62 
## F-statistic: 163.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 0.628288551716823 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0089 -0.7657  0.0583  0.8966  3.4414 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99285    0.08648 115.545  < 2e-16 ***
## category_code_LT01_3_count   0.25415    0.11640   2.183 0.029481 *  
## category_code_LT01_4_count   0.75163    0.09325   8.060 5.83e-15 ***
## category_code_LT01_5_count   0.91053    0.06154  14.795  < 2e-16 ***
## category_code_LT01_9_count   0.38242    0.22500   1.700 0.089831 .  
## category_code_LT01_11_count  0.38395    0.11289   3.401 0.000725 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 492 degrees of freedom
## Multiple R-squared:  0.632,  Adjusted R-squared:  0.6283 
## F-statistic:   169 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 0.619921060843282 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0042 -0.7762  0.0499  0.8922  3.4450 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98660    0.08745 114.201  < 2e-16 ***
## category_code_LT01_3_count   0.34725    0.11430   3.038  0.00251 ** 
## category_code_LT01_4_count   0.90087    0.08279  10.882  < 2e-16 ***
## category_code_LT01_5_count   0.91289    0.06247  14.613  < 2e-16 ***
## category_code_LT01_9_count   0.42949    0.22707   1.891  0.05915 .  
## category_code_LT01_12_count  0.14277    0.20558   0.694  0.48773    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6199 
## F-statistic: 163.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 0.619853914060397 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0067 -0.7744  0.0625  0.8845  3.4414 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98711    0.08745 114.207  < 2e-16 ***
## category_code_LT01_3_count   0.35165    0.11398   3.085  0.00215 ** 
## category_code_LT01_4_count   0.90285    0.08253  10.940  < 2e-16 ***
## category_code_LT01_5_count   0.91573    0.06224  14.713  < 2e-16 ***
## category_code_LT01_9_count   0.43992    0.22750   1.934  0.05372 .  
## category_code_LT01_13_count  0.15361    0.24433   0.629  0.52983    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6199 
## F-statistic: 163.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 0.619696789507269 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0076 -0.7671  0.0524  0.8813  3.4412 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98907    0.08754 114.112  < 2e-16 ***
## category_code_LT01_3_count   0.35636    0.11410   3.123  0.00189 ** 
## category_code_LT01_4_count   0.90266    0.08359  10.799  < 2e-16 ***
## category_code_LT01_5_count   0.91411    0.06255  14.615  < 2e-16 ***
## category_code_LT01_9_count   0.42360    0.22779   1.860  0.06354 .  
## category_code_LT01_14_count  0.14432    0.32950   0.438  0.66158    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6197 
## F-statistic:   163 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 0.619551060130201 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0080 -0.7686  0.0496  0.8842  3.4396 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98752    0.08748 114.166  < 2e-16 ***
## category_code_LT01_3_count   0.35289    0.11504   3.068  0.00228 ** 
## category_code_LT01_4_count   0.91015    0.08191  11.112  < 2e-16 ***
## category_code_LT01_5_count   0.91697    0.06225  14.730  < 2e-16 ***
## category_code_LT01_9_count   0.43169    0.22732   1.899  0.05815 .  
## category_code_LT01_15_count  0.04358    0.75787   0.058  0.95417    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6234, Adjusted R-squared:  0.6196 
## F-statistic: 162.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 0.619833800918763 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0079 -0.7681  0.0467  0.8850  3.4400 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98794    0.08745 114.212  < 2e-16 ***
## category_code_LT01_3_count   0.34544    0.11475   3.010  0.00274 ** 
## category_code_LT01_4_count   0.91156    0.08164  11.166  < 2e-16 ***
## category_code_LT01_5_count   0.91623    0.06222  14.725  < 2e-16 ***
## category_code_LT01_9_count   0.42740    0.22717   1.881  0.06051 .  
## category_code_LT01_16_count  0.71415    1.17529   0.608  0.54371    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6198 
## F-statistic: 163.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 0.626706931681075 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9969 -0.7579  0.0515  0.8791  3.3401 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97601    0.08990 110.965  < 2e-16 ***
## category_code_LT01_3_count   0.26326    0.11733   2.244  0.02529 *  
## category_code_LT01_4_count   0.75956    0.09329   8.142 3.22e-15 ***
## category_code_LT01_5_count   0.91751    0.06153  14.911  < 2e-16 ***
## category_code_LT01_10_count  0.10056    0.11300   0.890  0.37394    
## category_code_LT01_11_count  0.39391    0.11292   3.488  0.00053 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 492 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.6267 
## F-statistic: 167.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 0.617832025433061 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9922 -0.7585  0.0527  0.8820  3.3366 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96892    0.09094 109.616  < 2e-16 ***
## category_code_LT01_3_count   0.36181    0.11512   3.143  0.00177 ** 
## category_code_LT01_4_count   0.91494    0.08257  11.081  < 2e-16 ***
## category_code_LT01_5_count   0.92104    0.06249  14.739  < 2e-16 ***
## category_code_LT01_10_count  0.10661    0.11439   0.932  0.35180    
## category_code_LT01_12_count  0.13996    0.20627   0.679  0.49777    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6178 
## F-statistic: 161.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 0.617656087217571 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9948 -0.7589  0.0532  0.8682  3.3313 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96933    0.09096 109.596  < 2e-16 ***
## category_code_LT01_3_count   0.36701    0.11481   3.197  0.00148 ** 
## category_code_LT01_4_count   0.91879    0.08222  11.174  < 2e-16 ***
## category_code_LT01_5_count   0.92423    0.06225  14.846  < 2e-16 ***
## category_code_LT01_10_count  0.10788    0.11438   0.943  0.34605    
## category_code_LT01_13_count  0.11830    0.24467   0.483  0.62896    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6215, Adjusted R-squared:  0.6177 
## F-statistic: 161.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 0.617582663122339 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9969 -0.7617  0.0565  0.8695  3.3391 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97261    0.09143 109.074  < 2e-16 ***
## category_code_LT01_3_count   0.37140    0.11521   3.224  0.00135 ** 
## category_code_LT01_4_count   0.91761    0.08340  11.002  < 2e-16 ***
## category_code_LT01_5_count   0.92245    0.06261  14.733  < 2e-16 ***
## category_code_LT01_10_count  0.09954    0.11739   0.848  0.39686    
## category_code_LT01_14_count  0.12621    0.33822   0.373  0.70918    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6176 
## F-statistic: 161.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 0.617478319852585 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9950 -0.7586  0.0478  0.8706  3.3286 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96906    0.09101 109.538  < 2e-16 ***
## category_code_LT01_3_count   0.36880    0.11564   3.189  0.00152 ** 
## category_code_LT01_4_count   0.92476    0.08164  11.327  < 2e-16 ***
## category_code_LT01_5_count   0.92488    0.06227  14.853  < 2e-16 ***
## category_code_LT01_10_count  0.10995    0.11458   0.960  0.33774    
## category_code_LT01_15_count -0.05390    0.76083  -0.071  0.94355    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6175 
## F-statistic: 161.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 0.617784204755381 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9956 -0.7596  0.0447  0.8786  3.3311 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97006    0.09096 109.610   <2e-16 ***
## category_code_LT01_3_count   0.35919    0.11559   3.107    0.002 ** 
## category_code_LT01_4_count   0.92534    0.08142  11.365   <2e-16 ***
## category_code_LT01_5_count   0.92423    0.06224  14.850   <2e-16 ***
## category_code_LT01_10_count  0.10743    0.11436   0.939    0.348    
## category_code_LT01_16_count  0.74418    1.17847   0.631    0.528    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.6178 
## F-statistic: 161.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 0.626136691026662 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0195 -0.7617  0.0476  0.8757  3.4274 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99776    0.08671 115.301  < 2e-16 ***
## category_code_LT01_3_count   0.28178    0.11563   2.437 0.015169 *  
## category_code_LT01_4_count   0.76320    0.09330   8.180 2.44e-15 ***
## category_code_LT01_5_count   0.91877    0.06181  14.864  < 2e-16 ***
## category_code_LT01_11_count  0.40231    0.11703   3.438 0.000637 ***
## category_code_LT01_12_count -0.04241    0.21119  -0.201 0.840943    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6261 
## F-statistic: 167.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 0.62618339566163 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0179 -0.7584  0.0503  0.8773  3.4296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99725    0.08669 115.323  < 2e-16 ***
## category_code_LT01_3_count   0.28127    0.11561   2.433  0.01534 *  
## category_code_LT01_4_count   0.76007    0.09370   8.112 4.01e-15 ***
## category_code_LT01_5_count   0.91723    0.06159  14.892  < 2e-16 ***
## category_code_LT01_11_count  0.39415    0.11315   3.483  0.00054 ***
## category_code_LT01_13_count  0.07728    0.24222   0.319  0.74982    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6262 
## F-statistic: 167.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 0.626259883686552 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0178 -0.7554  0.0520  0.8734  3.4307 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99890    0.08674 115.273  < 2e-16 ***
## category_code_LT01_3_count   0.28398    0.11574   2.454 0.014489 *  
## category_code_LT01_4_count   0.75539    0.09475   7.973 1.09e-14 ***
## category_code_LT01_5_count   0.91475    0.06191  14.775  < 2e-16 ***
## category_code_LT01_11_count  0.39419    0.11305   3.487 0.000532 ***
## category_code_LT01_14_count  0.14668    0.32594   0.450 0.652905    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6263 
## F-statistic: 167.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 0.62611869868685 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0182 -0.7589  0.0445  0.8770  3.4292 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                   9.9973     0.0867 115.314  < 2e-16 ***
## category_code_LT01_3_count    0.2832     0.1164   2.432 0.015358 *  
## category_code_LT01_4_count    0.7635     0.0934   8.174 2.54e-15 ***
## category_code_LT01_5_count    0.9175     0.0616  14.894  < 2e-16 ***
## category_code_LT01_11_count   0.3967     0.1130   3.509 0.000491 ***
## category_code_LT01_15_count  -0.0969     0.7512  -0.129 0.897414    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6261 
## F-statistic: 167.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 0.626413242492989 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0183 -0.7576  0.0464  0.8810  3.4294 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99782    0.08666 115.364  < 2e-16 ***
## category_code_LT01_3_count   0.27264    0.11641   2.342 0.019572 *  
## category_code_LT01_4_count   0.76404    0.09327   8.192 2.24e-15 ***
## category_code_LT01_5_count   0.91694    0.06157  14.894  < 2e-16 ***
## category_code_LT01_11_count  0.39557    0.11294   3.502 0.000503 ***
## category_code_LT01_16_count  0.74079    1.16467   0.636 0.525041    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6264 
## F-statistic: 167.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 0.617344413206155 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0142 -0.7639  0.0470  0.8730  3.4321 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99133    0.08771 113.919  < 2e-16 ***
## category_code_LT01_3_count   0.38042    0.11327   3.359 0.000844 ***
## category_code_LT01_4_count   0.91347    0.08327  10.970  < 2e-16 ***
## category_code_LT01_5_count   0.92038    0.06255  14.715  < 2e-16 ***
## category_code_LT01_12_count  0.14417    0.20634   0.699 0.485083    
## category_code_LT01_13_count  0.12005    0.24477   0.490 0.624027    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6173 
## F-statistic: 161.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 0.617371440634914 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0144 -0.7693  0.0520  0.8713  3.4329 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99337    0.08777 113.856  < 2e-16 ***
## category_code_LT01_3_count   0.38417    0.11337   3.389 0.000758 ***
## category_code_LT01_4_count   0.90973    0.08437  10.782  < 2e-16 ***
## category_code_LT01_5_count   0.91780    0.06284  14.606  < 2e-16 ***
## category_code_LT01_12_count  0.13835    0.20691   0.669 0.504034    
## category_code_LT01_14_count  0.17347    0.33060   0.525 0.600021    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6174 
## F-statistic: 161.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 0.61715734226311 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0149 -0.7712  0.0357  0.8764  3.4311 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.991530   0.087728 113.892  < 2e-16 ***
## category_code_LT01_3_count  0.381341   0.114295   3.336 0.000913 ***
## category_code_LT01_4_count  0.918952   0.082782  11.101  < 2e-16 ***
## category_code_LT01_5_count  0.921080   0.062563  14.723  < 2e-16 ***
## category_code_LT01_12_count 0.147023   0.206374   0.712 0.476549    
## category_code_LT01_15_count 0.003727   0.759961   0.005 0.996089    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6172 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 0.617500462160083 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0147 -0.7628  0.0307  0.8804  3.4316 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99196    0.08769 113.948   <2e-16 ***
## category_code_LT01_3_count   0.37187    0.11413   3.258   0.0012 ** 
## category_code_LT01_4_count   0.91985    0.08250  11.149   <2e-16 ***
## category_code_LT01_5_count   0.92023    0.06253  14.716   <2e-16 ***
## category_code_LT01_12_count  0.14826    0.20623   0.719   0.4725    
## category_code_LT01_16_count  0.78294    1.17849   0.664   0.5068    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6175 
## F-statistic: 161.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 0.617226373158148 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0172 -0.7624  0.0479  0.8661  3.4290 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99421    0.08777  113.86  < 2e-16 ***
## category_code_LT01_3_count   0.38972    0.11297    3.45 0.000609 ***
## category_code_LT01_4_count   0.91221    0.08425   10.83  < 2e-16 ***
## category_code_LT01_5_count   0.92055    0.06265   14.69  < 2e-16 ***
## category_code_LT01_13_count  0.12489    0.24471    0.51 0.610036    
## category_code_LT01_14_count  0.19114    0.32961    0.58 0.562251    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6172 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 0.61696508937077 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0179 -0.7749  0.0371  0.8610  3.4267 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99225    0.08774 113.883  < 2e-16 ***
## category_code_LT01_3_count   0.38681    0.11393   3.395 0.000741 ***
## category_code_LT01_4_count   0.92292    0.08246  11.192  < 2e-16 ***
## category_code_LT01_5_count   0.92445    0.06233  14.832  < 2e-16 ***
## category_code_LT01_13_count  0.12517    0.24532   0.510 0.610124    
## category_code_LT01_15_count  0.01589    0.76154   0.021 0.983363    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.617 
## F-statistic: 161.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617320622475232 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0177 -0.7752  0.0341  0.8640  3.4272 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99268    0.08770 113.941  < 2e-16 ***
## category_code_LT01_3_count   0.37740    0.11378   3.317 0.000977 ***
## category_code_LT01_4_count   0.92375    0.08214  11.246  < 2e-16 ***
## category_code_LT01_5_count   0.92356    0.06229  14.826  < 2e-16 ***
## category_code_LT01_13_count  0.13079    0.24484   0.534 0.593445    
## category_code_LT01_16_count  0.79782    1.17948   0.676 0.499096    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6173 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 0.617024122928217 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0179 -0.7593  0.0374  0.8650  3.4279 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99443    0.08780 113.833  < 2e-16 ***
## category_code_LT01_3_count   0.39122    0.11397   3.433 0.000648 ***
## category_code_LT01_4_count   0.91828    0.08366  10.976  < 2e-16 ***
## category_code_LT01_5_count   0.92132    0.06266  14.702  < 2e-16 ***
## category_code_LT01_14_count  0.19120    0.32974   0.580 0.562292    
## category_code_LT01_15_count -0.01687    0.75998  -0.022 0.982299    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.617 
## F-statistic: 161.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617387021816729 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0178 -0.7645  0.0336  0.8640  3.4285 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99499    0.08776 113.891  < 2e-16 ***
## category_code_LT01_3_count   0.38125    0.11380   3.350 0.000869 ***
## category_code_LT01_4_count   0.91858    0.08343  11.011  < 2e-16 ***
## category_code_LT01_5_count   0.92033    0.06263  14.694  < 2e-16 ***
## category_code_LT01_14_count  0.20086    0.32985   0.609 0.542849    
## category_code_LT01_16_count  0.80632    1.17973   0.683 0.494626    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6174 
## F-statistic: 161.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 0.61709887776991 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0186 -0.7775  0.0308  0.8602  3.4260 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99292    0.08773 113.908  < 2e-16 ***
## category_code_LT01_3_count   0.37864    0.11484   3.297  0.00105 ** 
## category_code_LT01_4_count   0.92984    0.08157  11.400  < 2e-16 ***
## category_code_LT01_5_count   0.92445    0.06231  14.837  < 2e-16 ***
## category_code_LT01_15_count  0.01266    0.76054   0.017  0.98673    
## category_code_LT01_16_count  0.77601    1.18021   0.658  0.51116    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6171 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 0.601183688089584 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0699 -0.8255  0.0647  0.9275  3.7711 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.02988    0.08945 112.134  < 2e-16 ***
## category_code_LT01_3_count   0.53232    0.11244   4.734 2.88e-06 ***
## category_code_LT01_5_count   0.94514    0.06354  14.875  < 2e-16 ***
## category_code_LT01_6_count   0.62064    0.15301   4.056 5.80e-05 ***
## category_code_LT01_7_count   0.61781    0.15974   3.868 0.000125 ***
## category_code_LT01_11_count  0.57110    0.11348   5.033 6.80e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.422 on 492 degrees of freedom
## Multiple R-squared:  0.6052, Adjusted R-squared:  0.6012 
## F-statistic: 150.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 0.625540532690894 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0089 -0.7684  0.0136  0.9141  4.0512 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.99065    0.08684 115.045  < 2e-16 ***
## category_code_LT01_4_count  0.87042    0.07951  10.947  < 2e-16 ***
## category_code_LT01_5_count  0.91381    0.06253  14.615  < 2e-16 ***
## category_code_LT01_6_count  0.50341    0.14910   3.376 0.000793 ***
## category_code_LT01_7_count  0.51990    0.15278   3.403 0.000721 ***
## category_code_LT01_8_count -0.19436    0.27311  -0.712 0.477011    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 492 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6255 
## F-statistic:   167 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 0.627735909557418 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9918 -0.7564  0.0018  0.9150  4.0585 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.98339    0.08660 115.279  < 2e-16 ***
## category_code_LT01_4_count  0.84976    0.08008  10.611  < 2e-16 ***
## category_code_LT01_5_count  0.89950    0.06184  14.546  < 2e-16 ***
## category_code_LT01_6_count  0.47965    0.14893   3.221  0.00136 ** 
## category_code_LT01_7_count  0.48564    0.15317   3.171  0.00162 ** 
## category_code_LT01_9_count  0.41327    0.22377   1.847  0.06537 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 492 degrees of freedom
## Multiple R-squared:  0.6315, Adjusted R-squared:  0.6277 
## F-statistic: 168.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 0.625579839816333 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9850 -0.7546  0.0193  0.9100  3.9780 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97097    0.09006 110.720  < 2e-16 ***
## category_code_LT01_4_count   0.86674    0.07968  10.877  < 2e-16 ***
## category_code_LT01_5_count   0.90761    0.06187  14.669  < 2e-16 ***
## category_code_LT01_6_count   0.48028    0.15114   3.178  0.00158 ** 
## category_code_LT01_7_count   0.50670    0.15326   3.306  0.00101 ** 
## category_code_LT01_10_count  0.08458    0.11321   0.747  0.45536    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 492 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6256 
## F-statistic: 167.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 0.631711646853191 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0038 -0.7473  0.0276  0.9658  3.8152 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99258    0.08610 116.063  < 2e-16 ***
## category_code_LT01_4_count   0.73531    0.09117   8.066  5.6e-15 ***
## category_code_LT01_5_count   0.90362    0.06137  14.723  < 2e-16 ***
## category_code_LT01_6_count   0.41359    0.15057   2.747  0.00624 ** 
## category_code_LT01_7_count   0.39604    0.15682   2.526  0.01187 *  
## category_code_LT01_11_count  0.33771    0.11411   2.960  0.00323 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 492 degrees of freedom
## Multiple R-squared:  0.6354, Adjusted R-squared:  0.6317 
## F-statistic: 171.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 0.625362461628698 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0003 -0.7522  0.0029  0.9245  4.0535 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98840    0.08683 115.032  < 2e-16 ***
## category_code_LT01_4_count   0.86387    0.08061  10.717  < 2e-16 ***
## category_code_LT01_5_count   0.90466    0.06211  14.565  < 2e-16 ***
## category_code_LT01_6_count   0.48915    0.15029   3.255 0.001213 ** 
## category_code_LT01_7_count   0.51523    0.15276   3.373 0.000803 ***
## category_code_LT01_12_count  0.10705    0.20511   0.522 0.601983    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6254 
## F-statistic: 166.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 0.625189851042125 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0024 -0.7579  0.0090  0.9200  4.0531 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98877    0.08685 115.014  < 2e-16 ***
## category_code_LT01_4_count   0.86881    0.08005  10.853  < 2e-16 ***
## category_code_LT01_5_count   0.90712    0.06192  14.651  < 2e-16 ***
## category_code_LT01_6_count   0.49968    0.14907   3.352 0.000864 ***
## category_code_LT01_7_count   0.51254    0.15388   3.331 0.000931 ***
## category_code_LT01_13_count  0.05211    0.24387   0.214 0.830879    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6252 
## F-statistic: 166.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 0.625348576500067 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0019 -0.7429  0.0171  0.9177  4.0514 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99044    0.08688 114.988  < 2e-16 ***
## category_code_LT01_4_count   0.86200    0.08139  10.591  < 2e-16 ***
## category_code_LT01_5_count   0.90398    0.06226  14.519  < 2e-16 ***
## category_code_LT01_6_count   0.50599    0.14961   3.382 0.000777 ***
## category_code_LT01_7_count   0.51089    0.15315   3.336 0.000914 ***
## category_code_LT01_14_count  0.16531    0.32793   0.504 0.614412    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6253 
## F-statistic: 166.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 0.625246458017848 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0031 -0.7598  0.0083  0.9105  4.0529 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98896    0.08684 115.027  < 2e-16 ***
## category_code_LT01_4_count   0.86676    0.08036  10.786  < 2e-16 ***
## category_code_LT01_5_count   0.90778    0.06191  14.664  < 2e-16 ***
## category_code_LT01_6_count   0.49645    0.14928   3.326 0.000948 ***
## category_code_LT01_7_count   0.51786    0.15282   3.389 0.000759 ***
## category_code_LT01_15_count  0.25858    0.74651   0.346 0.729197    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6252 
## F-statistic: 166.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 0.6264231712426 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0001 -0.7532  0.0219  0.9189  4.0536 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98830    0.08670 115.199  < 2e-16 ***
## category_code_LT01_4_count   0.86200    0.07970  10.815  < 2e-16 ***
## category_code_LT01_5_count   0.90442    0.06184  14.624  < 2e-16 ***
## category_code_LT01_6_count   0.51107    0.14909   3.428 0.000659 ***
## category_code_LT01_7_count   0.51553    0.15253   3.380 0.000783 ***
## category_code_LT01_16_count  1.49594    1.15756   1.292 0.196853    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6264 
## F-statistic: 167.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 0.62047557334787 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0046 -0.7747  0.0352  0.9420  4.0567 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.98514    0.08748 114.148  < 2e-16 ***
## category_code_LT01_4_count  0.94887    0.07446  12.744  < 2e-16 ***
## category_code_LT01_5_count  0.91546    0.06301  14.528  < 2e-16 ***
## category_code_LT01_6_count  0.48894    0.15047   3.249  0.00124 ** 
## category_code_LT01_8_count -0.18404    0.27494  -0.669  0.50358    
## category_code_LT01_9_count  0.49531    0.22470   2.204  0.02796 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 492 degrees of freedom
## Multiple R-squared:  0.6243, Adjusted R-squared:  0.6205 
## F-statistic: 163.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 0.617556107935007 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9930 -0.7875  0.0137  0.9028  3.9458 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96671    0.09102 109.496  < 2e-16 ***
## category_code_LT01_4_count   0.97343    0.07367  13.213  < 2e-16 ***
## category_code_LT01_5_count   0.92530    0.06310  14.664  < 2e-16 ***
## category_code_LT01_6_count   0.48616    0.15285   3.181  0.00156 ** 
## category_code_LT01_8_count  -0.16994    0.27590  -0.616  0.53821    
## category_code_LT01_10_count  0.11773    0.11402   1.033  0.30232    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6176 
## F-statistic: 161.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 0.627129109055393 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0154 -0.7577  0.0221  0.9585  3.7615 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99552    0.08666 115.339  < 2e-16 ***
## category_code_LT01_4_count   0.78560    0.08963   8.765  < 2e-16 ***
## category_code_LT01_5_count   0.91616    0.06235  14.694  < 2e-16 ***
## category_code_LT01_6_count   0.40507    0.15157   2.672 0.007780 ** 
## category_code_LT01_8_count  -0.13711    0.27250  -0.503 0.615077    
## category_code_LT01_11_count  0.41095    0.11092   3.705 0.000236 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6309, Adjusted R-squared:  0.6271 
## F-statistic: 168.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 0.61699665525537 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0152 -0.7936  0.0123  0.9325  4.0508 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99113    0.08783 113.755  < 2e-16 ***
## category_code_LT01_4_count   0.97378    0.07456  13.061  < 2e-16 ***
## category_code_LT01_5_count   0.92220    0.06335  14.557  < 2e-16 ***
## category_code_LT01_6_count   0.50132    0.15203   3.298  0.00105 ** 
## category_code_LT01_8_count  -0.17039    0.27621  -0.617  0.53761    
## category_code_LT01_12_count  0.12203    0.20747   0.588  0.55669    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.617 
## F-statistic: 161.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 0.616986367122211 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0165 -0.7808  0.0256  0.9179  4.0507 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99121    0.08783 113.756  < 2e-16 ***
## category_code_LT01_4_count   0.97438    0.07442  13.093  < 2e-16 ***
## category_code_LT01_5_count   0.92386    0.06319  14.621  < 2e-16 ***
## category_code_LT01_6_count   0.51340    0.15077   3.405 0.000715 ***
## category_code_LT01_8_count  -0.15602    0.27653  -0.564 0.572865    
## category_code_LT01_13_count  0.14141    0.24515   0.577 0.564330    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.617 
## F-statistic: 161.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 0.617165628893467 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0165 -0.7835  0.0362  0.9039  4.0479 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99398    0.08786 113.747  < 2e-16 ***
## category_code_LT01_4_count   0.96700    0.07589  12.741  < 2e-16 ***
## category_code_LT01_5_count   0.91997    0.06351  14.485  < 2e-16 ***
## category_code_LT01_6_count   0.52276    0.15131   3.455 0.000598 ***
## category_code_LT01_8_count  -0.16893    0.27605  -0.612 0.540851    
## category_code_LT01_14_count  0.24817    0.33068   0.750 0.453314    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6172 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 0.616780400196191 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0181 -0.7813  0.0298  0.9111  4.0502 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99171    0.08785 113.735  < 2e-16 ***
## category_code_LT01_4_count   0.97909    0.07407  13.218  < 2e-16 ***
## category_code_LT01_5_count   0.92552    0.06318  14.650  < 2e-16 ***
## category_code_LT01_6_count   0.51067    0.15103   3.381 0.000779 ***
## category_code_LT01_8_count  -0.16583    0.27616  -0.601 0.548445    
## category_code_LT01_15_count  0.19694    0.75467   0.261 0.794230    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.6168 
## F-statistic:   161 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 0.618095564220195 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0157 -0.7820  0.0231  0.9455  4.0507 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99121    0.08770 113.925  < 2e-16 ***
## category_code_LT01_4_count   0.97264    0.07350  13.234  < 2e-16 ***
## category_code_LT01_5_count   0.92271    0.06308  14.627  < 2e-16 ***
## category_code_LT01_6_count   0.52544    0.15085   3.483  0.00054 ***
## category_code_LT01_8_count  -0.18447    0.27605  -0.668  0.50430    
## category_code_LT01_16_count  1.55600    1.17200   1.328  0.18491    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6181 
## F-statistic: 161.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 0.620586909445745 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9806 -0.7562  0.0540  0.9273  3.9800 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96513    0.09064 109.944  < 2e-16 ***
## category_code_LT01_4_count   0.94384    0.07472  12.631  < 2e-16 ***
## category_code_LT01_5_count   0.90982    0.06235  14.591  < 2e-16 ***
## category_code_LT01_6_count   0.46624    0.15235   3.060  0.00233 ** 
## category_code_LT01_9_count   0.46973    0.22619   2.077  0.03835 *  
## category_code_LT01_10_count  0.08804    0.11438   0.770  0.44180    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 492 degrees of freedom
## Multiple R-squared:  0.6244, Adjusted R-squared:  0.6206 
## F-statistic: 163.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 0.629599765389811 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9994 -0.7565  0.0402  0.9586  3.7806 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98845    0.08640 115.612  < 2e-16 ***
## category_code_LT01_4_count   0.76563    0.08988   8.519  < 2e-16 ***
## category_code_LT01_5_count   0.90316    0.06163  14.654  < 2e-16 ***
## category_code_LT01_6_count   0.38613    0.15115   2.555 0.010933 *  
## category_code_LT01_9_count   0.41898    0.22279   1.881 0.060618 .  
## category_code_LT01_11_count  0.39358    0.11097   3.547 0.000428 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 492 degrees of freedom
## Multiple R-squared:  0.6333, Adjusted R-squared:  0.6296 
## F-statistic:   170 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 0.620353740148 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9963 -0.7730  0.0407  0.9371  4.0588 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98303    0.08746 114.142  < 2e-16 ***
## category_code_LT01_4_count   0.94150    0.07569  12.439  < 2e-16 ***
## category_code_LT01_5_count   0.90657    0.06259  14.483  < 2e-16 ***
## category_code_LT01_6_count   0.47474    0.15165   3.131  0.00185 ** 
## category_code_LT01_9_count   0.48882    0.22465   2.176  0.03004 *  
## category_code_LT01_12_count  0.11119    0.20648   0.539  0.59046    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 492 degrees of freedom
## Multiple R-squared:  0.6242, Adjusted R-squared:  0.6204 
## F-statistic: 163.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 0.620549263981587 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9971 -0.7725  0.0338  0.9008  4.0589 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98294    0.08744 114.172  < 2e-16 ***
## category_code_LT01_4_count   0.93863    0.07571  12.397  < 2e-16 ***
## category_code_LT01_5_count   0.90792    0.06239  14.553  < 2e-16 ***
## category_code_LT01_6_count   0.48577    0.15035   3.231  0.00132 ** 
## category_code_LT01_9_count   0.49997    0.22493   2.223  0.02668 *  
## category_code_LT01_13_count  0.17991    0.24400   0.737  0.46126    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 492 degrees of freedom
## Multiple R-squared:  0.6244, Adjusted R-squared:  0.6205 
## F-statistic: 163.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 0.620388377061166 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9980 -0.7750  0.0283  0.9300  4.0564 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98543    0.08751 114.100  < 2e-16 ***
## category_code_LT01_4_count   0.93797    0.07678  12.217  < 2e-16 ***
## category_code_LT01_5_count   0.90551    0.06273  14.435  < 2e-16 ***
## category_code_LT01_6_count   0.49331    0.15103   3.266  0.00117 ** 
## category_code_LT01_9_count   0.48074    0.22526   2.134  0.03333 *  
## category_code_LT01_14_count  0.19109    0.33018   0.579  0.56304    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 492 degrees of freedom
## Multiple R-squared:  0.6242, Adjusted R-squared:  0.6204 
## F-statistic: 163.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 0.620198683791501 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9990 -0.7911  0.0292  0.9139  4.0583 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98358    0.08747 114.131  < 2e-16 ***
## category_code_LT01_4_count   0.94551    0.07529  12.559  < 2e-16 ***
## category_code_LT01_5_count   0.90974    0.06239  14.581  < 2e-16 ***
## category_code_LT01_6_count   0.48271    0.15066   3.204  0.00144 ** 
## category_code_LT01_9_count   0.49191    0.22471   2.189  0.02906 *  
## category_code_LT01_15_count  0.22420    0.75140   0.298  0.76554    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 492 degrees of freedom
## Multiple R-squared:  0.624,  Adjusted R-squared:  0.6202 
## F-statistic: 163.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 0.621216571217796 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9967 -0.7852  0.0331  0.9233  4.0587 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98316    0.08736 114.279  < 2e-16 ***
## category_code_LT01_4_count   0.94143    0.07464  12.612  < 2e-16 ***
## category_code_LT01_5_count   0.90692    0.06233  14.549  < 2e-16 ***
## category_code_LT01_6_count   0.49678    0.15053   3.300  0.00104 ** 
## category_code_LT01_9_count   0.47682    0.22467   2.122  0.03431 *  
## category_code_LT01_16_count  1.38660    1.16715   1.188  0.23540    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 492 degrees of freedom
## Multiple R-squared:  0.625,  Adjusted R-squared:  0.6212 
## F-statistic:   164 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 0.627537200456219 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9897 -0.7449 -0.0102  0.9383  3.6756 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97298    0.08983 111.023  < 2e-16 ***
## category_code_LT01_4_count   0.77920    0.08976   8.681  < 2e-16 ***
## category_code_LT01_5_count   0.91159    0.06164  14.789  < 2e-16 ***
## category_code_LT01_6_count   0.37996    0.15331   2.478 0.013531 *  
## category_code_LT01_10_count  0.10023    0.11259   0.890 0.373777    
## category_code_LT01_11_count  0.40861    0.11091   3.684 0.000255 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6275 
## F-statistic: 168.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 0.617486376264308 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9856 -0.7666  0.0015  0.9243  3.9506 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96529    0.09101 109.499  < 2e-16 ***
## category_code_LT01_4_count   0.96585    0.07491  12.893  < 2e-16 ***
## category_code_LT01_5_count   0.91674    0.06266  14.631  < 2e-16 ***
## category_code_LT01_6_count   0.47259    0.15394   3.070  0.00226 ** 
## category_code_LT01_10_count  0.11469    0.11407   1.005  0.31518    
## category_code_LT01_12_count  0.11158    0.20733   0.538  0.59070    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6175 
## F-statistic: 161.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 0.617519613800433 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9871 -0.7698  0.0040  0.9080  3.9507 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96553    0.09100 109.506  < 2e-16 ***
## category_code_LT01_4_count   0.96583    0.07476  12.919  < 2e-16 ***
## category_code_LT01_5_count   0.91861    0.06245  14.710  < 2e-16 ***
## category_code_LT01_6_count   0.48407    0.15278   3.169  0.00163 ** 
## category_code_LT01_10_count  0.11434    0.11407   1.002  0.31666    
## category_code_LT01_13_count  0.14109    0.24472   0.577  0.56450    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6175 
## F-statistic: 161.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 0.617467586503103 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9897 -0.7682 -0.0001  0.9040  3.9593 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97004    0.09145 109.021  < 2e-16 ***
## category_code_LT01_4_count   0.96364    0.07595  12.687  < 2e-16 ***
## category_code_LT01_5_count   0.91586    0.06286  14.571  < 2e-16 ***
## category_code_LT01_6_count   0.49295    0.15404   3.200  0.00146 ** 
## category_code_LT01_10_count  0.10244    0.11726   0.874  0.38277    
## category_code_LT01_14_count  0.17512    0.33990   0.515  0.60663    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6175 
## F-statistic: 161.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 0.617286018749587 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9883 -0.7765 -0.0071  0.9063  3.9498 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96578    0.09105 109.448  < 2e-16 ***
## category_code_LT01_4_count   0.97134    0.07439  13.057  < 2e-16 ***
## category_code_LT01_5_count   0.91984    0.06246  14.728  < 2e-16 ***
## category_code_LT01_6_count   0.48166    0.15294   3.149  0.00174 ** 
## category_code_LT01_10_count  0.11500    0.11437   1.006  0.31514    
## category_code_LT01_15_count  0.13511    0.75631   0.179  0.85829    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6173 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 0.618441657040354 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9870 -0.7765 -0.0047  0.9195  3.9567 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96669    0.09090 109.645  < 2e-16 ***
## category_code_LT01_4_count   0.96514    0.07387  13.065  < 2e-16 ***
## category_code_LT01_5_count   0.91673    0.06239  14.693  < 2e-16 ***
## category_code_LT01_6_count   0.49612    0.15296   3.243  0.00126 ** 
## category_code_LT01_10_count  0.10783    0.11409   0.945  0.34507    
## category_code_LT01_16_count  1.44608    1.17210   1.234  0.21788    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 492 degrees of freedom
## Multiple R-squared:  0.6223, Adjusted R-squared:  0.6184 
## F-statistic: 162.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 0.627050151080891 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0128 -0.7368  0.0178  0.9595  3.7533 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99478    0.08665 115.351  < 2e-16 ***
## category_code_LT01_4_count   0.78460    0.08962   8.755  < 2e-16 ***
## category_code_LT01_5_count   0.91345    0.06188  14.762  < 2e-16 ***
## category_code_LT01_6_count   0.40656    0.15196   2.675 0.007712 ** 
## category_code_LT01_11_count  0.42380    0.11469   3.695 0.000245 ***
## category_code_LT01_12_count -0.08168    0.21163  -0.386 0.699704    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6308, Adjusted R-squared:  0.6271 
## F-statistic: 168.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 0.62705036025043 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0103 -0.7434  0.0266  0.9620  3.7638 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99403    0.08664 115.352  < 2e-16 ***
## category_code_LT01_4_count   0.78089    0.09012   8.665  < 2e-16 ***
## category_code_LT01_5_count   0.91093    0.06170  14.763  < 2e-16 ***
## category_code_LT01_6_count   0.40295    0.15148   2.660 0.008066 ** 
## category_code_LT01_11_count  0.40981    0.11111   3.688 0.000251 ***
## category_code_LT01_13_count  0.09348    0.24199   0.386 0.699440    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6308, Adjusted R-squared:  0.6271 
## F-statistic: 168.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 0.627195065711485 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0099 -0.7477  0.0310  0.9276  3.7619 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99603    0.08667 115.333  < 2e-16 ***
## category_code_LT01_4_count   0.77451    0.09124   8.488 2.49e-16 ***
## category_code_LT01_5_count   0.90751    0.06206  14.624  < 2e-16 ***
## category_code_LT01_6_count   0.41005    0.15209   2.696 0.007254 ** 
## category_code_LT01_11_count  0.40960    0.11098   3.691 0.000249 ***
## category_code_LT01_14_count  0.19051    0.32659   0.583 0.559947    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6309, Adjusted R-squared:  0.6272 
## F-statistic: 168.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 0.62693888604128 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0111 -0.7449  0.0147  0.9600  3.7619 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99430    0.08665 115.341  < 2e-16 ***
## category_code_LT01_4_count   0.78421    0.08995   8.718  < 2e-16 ***
## category_code_LT01_5_count   0.91161    0.06170  14.774  < 2e-16 ***
## category_code_LT01_6_count   0.40143    0.15161   2.648  0.00836 ** 
## category_code_LT01_11_count  0.41220    0.11109   3.710  0.00023 ***
## category_code_LT01_15_count  0.03474    0.74578   0.047  0.96286    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 492 degrees of freedom
## Multiple R-squared:  0.6307, Adjusted R-squared:  0.6269 
## F-statistic:   168 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 0.627872746389802 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0087 -0.7397  0.0353  0.9535  3.7669 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99371    0.08654 115.477  < 2e-16 ***
## category_code_LT01_4_count   0.78005    0.08961   8.705  < 2e-16 ***
## category_code_LT01_5_count   0.90910    0.06165  14.746  < 2e-16 ***
## category_code_LT01_6_count   0.41356    0.15165   2.727 0.006619 ** 
## category_code_LT01_11_count  0.40585    0.11093   3.659 0.000281 ***
## category_code_LT01_16_count  1.28672    1.15698   1.112 0.266620    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 492 degrees of freedom
## Multiple R-squared:  0.6316, Adjusted R-squared:  0.6279 
## F-statistic: 168.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 0.61697400212419 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0088 -0.7849  0.0183  0.9467  4.0526 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98925    0.08780 113.773  < 2e-16 ***
## category_code_LT01_4_count   0.96625    0.07561  12.780  < 2e-16 ***
## category_code_LT01_5_count   0.91567    0.06272  14.599  < 2e-16 ***
## category_code_LT01_6_count   0.49922    0.15195   3.285  0.00109 ** 
## category_code_LT01_12_count  0.11410    0.20747   0.550  0.58260    
## category_code_LT01_13_count  0.14516    0.24487   0.593  0.55359    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.617 
## F-statistic: 161.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 0.617073026934626 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0088 -0.7813 -0.0010  0.9237  4.0501 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99179    0.08784 113.746  < 2e-16 ***
## category_code_LT01_4_count   0.96074    0.07686  12.500  < 2e-16 ***
## category_code_LT01_5_count   0.91200    0.06305  14.466  < 2e-16 ***
## category_code_LT01_6_count   0.50839    0.15265   3.330 0.000933 ***
## category_code_LT01_12_count  0.10520    0.20815   0.505 0.613512    
## category_code_LT01_14_count  0.22968    0.33196   0.692 0.489324    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.6171 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 0.616755894516489 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0101 -0.7866 -0.0006  0.9454  4.0522 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98965    0.08782 113.748  < 2e-16 ***
## category_code_LT01_4_count   0.97075    0.07539  12.877  < 2e-16 ***
## category_code_LT01_5_count   0.91690    0.06273  14.617  < 2e-16 ***
## category_code_LT01_6_count   0.49574    0.15223   3.257  0.00121 ** 
## category_code_LT01_12_count  0.11902    0.20747   0.574  0.56644    
## category_code_LT01_15_count  0.20142    0.75481   0.267  0.78970    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.6168 
## F-statistic:   161 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 0.617989806007757 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0072 -0.7847  0.0077  0.9601  4.0529 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98901    0.08768 113.923  < 2e-16 ***
## category_code_LT01_4_count   0.96485    0.07477  12.903  < 2e-16 ***
## category_code_LT01_5_count   0.91365    0.06266  14.581  < 2e-16 ***
## category_code_LT01_6_count   0.51013    0.15203   3.356 0.000853 ***
## category_code_LT01_12_count  0.11535    0.20710   0.557 0.577810    
## category_code_LT01_16_count  1.50848    1.17059   1.289 0.198125    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.618 
## F-statistic: 161.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 0.617165458503663 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0100 -0.7814  0.0190  0.9029  4.0498 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99204    0.08783 113.771  < 2e-16 ***
## category_code_LT01_4_count   0.95890    0.07700  12.453  < 2e-16 ***
## category_code_LT01_5_count   0.91332    0.06288  14.524  < 2e-16 ***
## category_code_LT01_6_count   0.51984    0.15119   3.438 0.000635 ***
## category_code_LT01_13_count  0.14970    0.24469   0.612 0.540969    
## category_code_LT01_14_count  0.24490    0.33063   0.741 0.459225    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6172 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616805613654495 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0116 -0.7794  0.0095  0.9075  4.0521 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98982    0.08781 113.761  < 2e-16 ***
## category_code_LT01_4_count   0.97023    0.07531  12.883  < 2e-16 ***
## category_code_LT01_5_count   0.91892    0.06252  14.699  < 2e-16 ***
## category_code_LT01_6_count   0.50770    0.15092   3.364 0.000828 ***
## category_code_LT01_13_count  0.15376    0.24527   0.627 0.531015    
## category_code_LT01_15_count  0.22186    0.75604   0.293 0.769305    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.6168 
## F-statistic:   161 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 0.618082089684085 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0085 -0.7787  0.0018  0.9404  4.0528 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98913    0.08767 113.942  < 2e-16 ***
## category_code_LT01_4_count   0.96384    0.07467  12.908  < 2e-16 ***
## category_code_LT01_5_count   0.91542    0.06245  14.658  < 2e-16 ***
## category_code_LT01_6_count   0.52225    0.15072   3.465 0.000577 ***
## category_code_LT01_13_count  0.16020    0.24454   0.655 0.512708    
## category_code_LT01_16_count  1.54065    1.17106   1.316 0.188922    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6181 
## F-statistic: 161.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616920339918048 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0114 -0.7820  0.0181  0.9151  4.0494 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99246    0.08785 113.742  < 2e-16 ***
## category_code_LT01_4_count   0.96432    0.07663  12.585  < 2e-16 ***
## category_code_LT01_5_count   0.91473    0.06289  14.544  < 2e-16 ***
## category_code_LT01_6_count   0.51693    0.15147   3.413 0.000696 ***
## category_code_LT01_14_count  0.24317    0.33078   0.735 0.462589    
## category_code_LT01_15_count  0.18363    0.75460   0.243 0.807841    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6169 
## F-statistic: 161.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 0.618259390276535 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0082 -0.7816  0.0191  0.9345  4.0499 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99201    0.08770 113.936  < 2e-16 ***
## category_code_LT01_4_count   0.95608    0.07621  12.545  < 2e-16 ***
## category_code_LT01_5_count   0.91076    0.06283  14.496  < 2e-16 ***
## category_code_LT01_6_count   0.53221    0.15130   3.518 0.000476 ***
## category_code_LT01_14_count  0.26817    0.33063   0.811 0.417706    
## category_code_LT01_16_count  1.56569    1.17181   1.336 0.182125    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6183 
## F-statistic:   162 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617812658913649 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0101 -0.7792  0.0019  0.9365  4.0523 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98961    0.08770 113.910  < 2e-16 ***
## category_code_LT01_4_count   0.96937    0.07432  13.043  < 2e-16 ***
## category_code_LT01_5_count   0.91696    0.06246  14.682  < 2e-16 ***
## category_code_LT01_6_count   0.51886    0.15098   3.437 0.000639 ***
## category_code_LT01_15_count  0.21588    0.75383   0.286 0.774712    
## category_code_LT01_16_count  1.52267    1.17114   1.300 0.194152    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6178 
## F-statistic: 161.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 0.620204932953105 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0328 -0.7947 -0.0254  0.8717  4.0367 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                10.00515    0.08729 114.624  < 2e-16 ***
## category_code_LT01_4_count  0.95687    0.07363  12.996  < 2e-16 ***
## category_code_LT01_5_count  0.92735    0.06276  14.776  < 2e-16 ***
## category_code_LT01_7_count  0.49430    0.15477   3.194  0.00149 ** 
## category_code_LT01_8_count -0.17624    0.27497  -0.641  0.52186    
## category_code_LT01_9_count  0.46920    0.22554   2.080  0.03802 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 492 degrees of freedom
## Multiple R-squared:  0.624,  Adjusted R-squared:  0.6202 
## F-statistic: 163.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 0.618177331581297 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0133 -0.7693  0.0227  0.8475  3.9010 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97976    0.09094 109.742  < 2e-16 ***
## category_code_LT01_4_count   0.97128    0.07335  13.242  < 2e-16 ***
## category_code_LT01_5_count   0.93582    0.06277  14.910  < 2e-16 ***
## category_code_LT01_7_count   0.51197    0.15483   3.307  0.00101 ** 
## category_code_LT01_8_count  -0.16609    0.27563  -0.603  0.54708    
## category_code_LT01_10_count  0.14662    0.11272   1.301  0.19395    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6182 
## F-statistic: 161.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 0.626238561625066 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0390 -0.7456  0.0346  0.9257  3.7552 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01186    0.08653 115.710  < 2e-16 ***
## category_code_LT01_4_count   0.80360    0.08851   9.079  < 2e-16 ***
## category_code_LT01_5_count   0.92657    0.06216  14.905  < 2e-16 ***
## category_code_LT01_7_count   0.38553    0.15802   2.440 0.015048 *  
## category_code_LT01_8_count  -0.13089    0.27276  -0.480 0.631548    
## category_code_LT01_11_count  0.39643    0.11285   3.513 0.000484 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6262 
## F-statistic: 167.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 0.6175857868623 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0409 -0.7879  0.0069  0.8634  4.0313 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01055    0.08754 114.357  < 2e-16 ***
## category_code_LT01_4_count   0.96877    0.07467  12.975  < 2e-16 ***
## category_code_LT01_5_count   0.93115    0.06308  14.760  < 2e-16 ***
## category_code_LT01_7_count   0.52693    0.15439   3.413 0.000696 ***
## category_code_LT01_8_count  -0.16843    0.27597  -0.610 0.541936    
## category_code_LT01_12_count  0.19811    0.20562   0.963 0.335778    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6176 
## F-statistic: 161.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 0.61687909827465 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0461 -0.7651  0.0069  0.8365  4.0298 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01210    0.08760 114.287  < 2e-16 ***
## category_code_LT01_4_count   0.98453    0.07315  13.459  < 2e-16 ***
## category_code_LT01_5_count   0.93655    0.06289  14.891  < 2e-16 ***
## category_code_LT01_7_count   0.52684    0.15567   3.384  0.00077 ***
## category_code_LT01_8_count  -0.15639    0.27657  -0.565  0.57202    
## category_code_LT01_13_count  0.03411    0.24702   0.138  0.89023    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.6169 
## F-statistic:   161 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 0.616898759949832 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0463 -0.7911  0.0081  0.8495  4.0289 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01297    0.08768 114.201  < 2e-16 ***
## category_code_LT01_4_count   0.98271    0.07403  13.274  < 2e-16 ***
## category_code_LT01_5_count   0.93552    0.06316  14.812  < 2e-16 ***
## category_code_LT01_7_count   0.52718    0.15489   3.404 0.000719 ***
## category_code_LT01_8_count  -0.15948    0.27605  -0.578 0.563727    
## category_code_LT01_14_count  0.06954    0.33033   0.211 0.833348    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6169 
## F-statistic: 161.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 0.617085029768527 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0467 -0.7581  0.0026  0.8554  4.0298 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01213    0.08758 114.321  < 2e-16 ***
## category_code_LT01_4_count   0.97856    0.07384  13.252  < 2e-16 ***
## category_code_LT01_5_count   0.93724    0.06286  14.911  < 2e-16 ***
## category_code_LT01_7_count   0.53154    0.15452   3.440 0.000631 ***
## category_code_LT01_8_count  -0.16055    0.27599  -0.582 0.561008    
## category_code_LT01_15_count  0.40132    0.75349   0.533 0.594543    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.6171 
## F-statistic: 161.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 0.617809603140667 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0454 -0.7579  0.0143  0.8619  4.0296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01227    0.08750 114.432  < 2e-16 ***
## category_code_LT01_4_count   0.98058    0.07269  13.490  < 2e-16 ***
## category_code_LT01_5_count   0.93524    0.06281  14.890  < 2e-16 ***
## category_code_LT01_7_count   0.52912    0.15432   3.429 0.000658 ***
## category_code_LT01_8_count  -0.17400    0.27605  -0.630 0.528787    
## category_code_LT01_16_count  1.29083    1.17011   1.103 0.270496    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6178 
## F-statistic: 161.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 0.62073654412524 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0009 -0.7667 -0.0158  0.8741  3.9339 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97758    0.09061 110.120   <2e-16 ***
## category_code_LT01_4_count   0.94664    0.07418  12.761   <2e-16 ***
## category_code_LT01_5_count   0.92107    0.06204  14.847   <2e-16 ***
## category_code_LT01_7_count   0.47939    0.15502   3.092   0.0021 ** 
## category_code_LT01_9_count   0.43574    0.22698   1.920   0.0555 .  
## category_code_LT01_10_count  0.11874    0.11316   1.049   0.2946    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 492 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:  0.6207 
## F-statistic: 163.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 0.628554510592841 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0226 -0.7414  0.0311  0.9111  3.7727 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00431    0.08628 115.948  < 2e-16 ***
## category_code_LT01_4_count   0.78470    0.08874   8.842  < 2e-16 ***
## category_code_LT01_5_count   0.91376    0.06144  14.873  < 2e-16 ***
## category_code_LT01_7_count   0.35763    0.15801   2.263  0.02405 *  
## category_code_LT01_9_count   0.40618    0.22362   1.816  0.06992 .  
## category_code_LT01_11_count  0.38216    0.11279   3.388  0.00076 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 492 degrees of freedom
## Multiple R-squared:  0.6323, Adjusted R-squared:  0.6286 
## F-statistic: 169.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 0.620511850486937 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0217 -0.7784 -0.0268  0.8923  4.0400 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00192    0.08723 114.663  < 2e-16 ***
## category_code_LT01_4_count   0.94105    0.07559  12.449  < 2e-16 ***
## category_code_LT01_5_count   0.91598    0.06235  14.690  < 2e-16 ***
## category_code_LT01_7_count   0.48930    0.15466   3.164  0.00165 ** 
## category_code_LT01_9_count   0.46023    0.22541   2.042  0.04170 *  
## category_code_LT01_12_count  0.18416    0.20475   0.899  0.36884    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 492 degrees of freedom
## Multiple R-squared:  0.6243, Adjusted R-squared:  0.6205 
## F-statistic: 163.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 0.619967538147897 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0264 -0.7838 -0.0227  0.8512  4.0387 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00322    0.08728 114.614  < 2e-16 ***
## category_code_LT01_4_count   0.95348    0.07428  12.836  < 2e-16 ***
## category_code_LT01_5_count   0.92094    0.06212  14.825  < 2e-16 ***
## category_code_LT01_7_count   0.48511    0.15601   3.110  0.00198 ** 
## category_code_LT01_9_count   0.46994    0.22608   2.079  0.03817 *  
## category_code_LT01_13_count  0.07908    0.24617   0.321  0.74816    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 492 degrees of freedom
## Multiple R-squared:  0.6238, Adjusted R-squared:   0.62 
## F-statistic: 163.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 0.619892414127504 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0270 -0.7888 -0.0271  0.8845  4.0381 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00376    0.08737 114.500  < 2e-16 ***
## category_code_LT01_4_count   0.95553    0.07488  12.760  < 2e-16 ***
## category_code_LT01_5_count   0.92100    0.06239  14.763  < 2e-16 ***
## category_code_LT01_7_count   0.49070    0.15508   3.164  0.00165 ** 
## category_code_LT01_9_count   0.46371    0.22596   2.052  0.04068 *  
## category_code_LT01_14_count  0.02541    0.32964   0.077  0.93859    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 492 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6199 
## F-statistic: 163.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 0.620124103612012 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0272 -0.7839 -0.0363  0.8685  4.0385 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00335    0.08726 114.643  < 2e-16 ***
## category_code_LT01_4_count   0.94905    0.07488  12.674  < 2e-16 ***
## category_code_LT01_5_count   0.92181    0.06209  14.846  < 2e-16 ***
## category_code_LT01_7_count   0.49346    0.15476   3.189  0.00152 ** 
## category_code_LT01_9_count   0.46633    0.22548   2.068  0.03915 *  
## category_code_LT01_15_count  0.41517    0.75050   0.553  0.58038    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 492 degrees of freedom
## Multiple R-squared:  0.6239, Adjusted R-squared:  0.6201 
## F-statistic: 163.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 0.62063019000512 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0260 -0.7825 -0.0276  0.8691  4.0383 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00356    0.08720 114.722  < 2e-16 ***
## category_code_LT01_4_count   0.95260    0.07370  12.926  < 2e-16 ***
## category_code_LT01_5_count   0.91983    0.06207  14.819  < 2e-16 ***
## category_code_LT01_7_count   0.49170    0.15462   3.180  0.00156 ** 
## category_code_LT01_9_count   0.45440    0.22556   2.015  0.04450 *  
## category_code_LT01_16_count  1.14371    1.16561   0.981  0.32697    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 492 degrees of freedom
## Multiple R-squared:  0.6244, Adjusted R-squared:  0.6206 
## F-statistic: 163.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 0.627031263093897 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0060 -0.7676  0.0475  0.8998  3.6494 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98263    0.08986 111.093  < 2e-16 ***
## category_code_LT01_4_count   0.79292    0.08879   8.931  < 2e-16 ***
## category_code_LT01_5_count   0.92117    0.06140  15.004  < 2e-16 ***
## category_code_LT01_7_count   0.36975    0.15814   2.338 0.019780 *  
## category_code_LT01_10_count  0.12599    0.11152   1.130 0.259114    
## category_code_LT01_11_count  0.39167    0.11283   3.472 0.000563 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 492 degrees of freedom
## Multiple R-squared:  0.6308, Adjusted R-squared:  0.627 
## F-statistic: 168.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 0.618495000258434 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0038 -0.7664  0.0034  0.8741  3.9099 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97794    0.09087 109.799  < 2e-16 ***
## category_code_LT01_4_count   0.95587    0.07528  12.698  < 2e-16 ***
## category_code_LT01_5_count   0.92477    0.06235  14.833  < 2e-16 ***
## category_code_LT01_7_count   0.50728    0.15471   3.279  0.00112 ** 
## category_code_LT01_10_count  0.14024    0.11279   1.243  0.21433    
## category_code_LT01_12_count  0.18068    0.20550   0.879  0.37970    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 492 degrees of freedom
## Multiple R-squared:  0.6223, Adjusted R-squared:  0.6185 
## F-statistic: 162.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 0.617912150222803 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0079 -0.7660  0.0237  0.8604  3.9043 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97842    0.09094 109.723  < 2e-16 ***
## category_code_LT01_4_count   0.96965    0.07385  13.129  < 2e-16 ***
## category_code_LT01_5_count   0.93001    0.06210  14.976  < 2e-16 ***
## category_code_LT01_7_count   0.50647    0.15589   3.249  0.00124 ** 
## category_code_LT01_10_count  0.14488    0.11276   1.285  0.19945    
## category_code_LT01_13_count  0.03600    0.24626   0.146  0.88384    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6179 
## F-statistic: 161.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 0.617899165395834 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0077 -0.7672  0.0198  0.8673  3.9027 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97779    0.09140 109.167  < 2e-16 ***
## category_code_LT01_4_count   0.97172    0.07440  13.061  < 2e-16 ***
## category_code_LT01_5_count   0.93060    0.06239  14.916  < 2e-16 ***
## category_code_LT01_7_count   0.50971    0.15504   3.288  0.00108 ** 
## category_code_LT01_10_count  0.14688    0.11530   1.274  0.20331    
## category_code_LT01_14_count -0.02301    0.33739  -0.068  0.94566    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6179 
## F-statistic: 161.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 0.618030186821983 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0091 -0.7688 -0.0147  0.8537  3.9076 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97925    0.09095 109.722  < 2e-16 ***
## category_code_LT01_4_count   0.96566    0.07443  12.975  < 2e-16 ***
## category_code_LT01_5_count   0.93051    0.06208  14.988  < 2e-16 ***
## category_code_LT01_7_count   0.51124    0.15488   3.301  0.00103 ** 
## category_code_LT01_10_count  0.14116    0.11314   1.248  0.21275    
## category_code_LT01_15_count  0.31454    0.75533   0.416  0.67728    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.618 
## F-statistic: 161.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 0.61868666793296 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0080 -0.7692  0.0109  0.8698  3.9090 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97963    0.09086 109.838  < 2e-16 ***
## category_code_LT01_4_count   0.96668    0.07342  13.167  < 2e-16 ***
## category_code_LT01_5_count   0.92833    0.06205  14.961  < 2e-16 ***
## category_code_LT01_7_count   0.50928    0.15466   3.293  0.00106 ** 
## category_code_LT01_10_count  0.13947    0.11276   1.237  0.21672    
## category_code_LT01_16_count  1.18087    1.16880   1.010  0.31284    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 492 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6187 
## F-statistic: 162.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 0.626064295001886 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0347 -0.7434  0.0422  0.9291  3.7547 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.010610   0.086523 115.699  < 2e-16 ***
## category_code_LT01_4_count   0.802549   0.088554   9.063  < 2e-16 ***
## category_code_LT01_5_count   0.922253   0.061728  14.941  < 2e-16 ***
## category_code_LT01_7_count   0.382342   0.158188   2.417 0.016012 *  
## category_code_LT01_11_count  0.398965   0.117463   3.397 0.000738 ***
## category_code_LT01_12_count -0.006201   0.211530  -0.029 0.976624    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6261 
## F-statistic: 167.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 0.626067320533028 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0345 -0.7432  0.0449  0.9302  3.7556 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01052    0.08650 115.723  < 2e-16 ***
## category_code_LT01_4_count   0.80197    0.08877   9.034  < 2e-16 ***
## category_code_LT01_5_count   0.92201    0.06148  14.996  < 2e-16 ***
## category_code_LT01_7_count   0.38141    0.15886   2.401 0.016726 *  
## category_code_LT01_11_count  0.39777    0.11288   3.524 0.000465 ***
## category_code_LT01_13_count  0.01695    0.24368   0.070 0.944563    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6261 
## F-statistic: 167.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 0.626086330406997 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0345 -0.7452  0.0461  0.9193  3.7549 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01118    0.08658 115.634  < 2e-16 ***
## category_code_LT01_4_count   0.80009    0.08955   8.934  < 2e-16 ***
## category_code_LT01_5_count   0.92103    0.06177  14.910  < 2e-16 ***
## category_code_LT01_7_count   0.38081    0.15827   2.406 0.016494 *  
## category_code_LT01_11_count  0.39783    0.11283   3.526 0.000462 ***
## category_code_LT01_14_count  0.05639    0.32634   0.173 0.862893    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6261 
## F-statistic: 167.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 0.626117596553103 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0347 -0.7422  0.0428  0.9257  3.7571 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01052    0.08650 115.733  < 2e-16 ***
## category_code_LT01_4_count   0.79994    0.08899   8.989  < 2e-16 ***
## category_code_LT01_5_count   0.92233    0.06147  15.004  < 2e-16 ***
## category_code_LT01_7_count   0.38444    0.15808   2.432 0.015371 *  
## category_code_LT01_11_count  0.39573    0.11315   3.498 0.000512 ***
## category_code_LT01_15_count  0.19894    0.74662   0.266 0.789998    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 492 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6261 
## F-statistic: 167.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 0.626733307486493 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0334 -0.7370  0.0530  0.9218  3.7586 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01050    0.08643 115.828  < 2e-16 ***
## category_code_LT01_4_count   0.80010    0.08845   9.045  < 2e-16 ***
## category_code_LT01_5_count   0.92044    0.06144  14.981  < 2e-16 ***
## category_code_LT01_7_count   0.38369    0.15780   2.431 0.015393 *  
## category_code_LT01_11_count  0.39359    0.11283   3.488 0.000529 ***
## category_code_LT01_16_count  1.08601    1.15593   0.940 0.347929    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 492 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.6267 
## F-statistic: 167.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 0.617313213520451 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0352 -0.7766  0.0193  0.8552  4.0330 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00885    0.08753 114.349  < 2e-16 ***
## category_code_LT01_4_count   0.96741    0.07514  12.875  < 2e-16 ***
## category_code_LT01_5_count   0.92540    0.06245  14.819  < 2e-16 ***
## category_code_LT01_7_count   0.52123    0.15547   3.353 0.000863 ***
## category_code_LT01_12_count  0.19271    0.20563   0.937 0.349150    
## category_code_LT01_13_count  0.03638    0.24650   0.148 0.882725    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6173 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 0.617310102368337 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0353 -0.7843  0.0202  0.8755  4.0325 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00942    0.08761 114.248  < 2e-16 ***
## category_code_LT01_4_count   0.96687    0.07583  12.750  < 2e-16 ***
## category_code_LT01_5_count   0.92479    0.06270  14.749  < 2e-16 ***
## category_code_LT01_7_count   0.52253    0.15474   3.377 0.000791 ***
## category_code_LT01_12_count  0.19149    0.20613   0.929 0.353373    
## category_code_LT01_14_count  0.04415    0.33106   0.133 0.893967    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6173 
## F-statistic: 161.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 0.617520833625359 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0355 -0.7735  0.0148  0.8710  4.0331 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00882    0.08750 114.381  < 2e-16 ***
## category_code_LT01_4_count   0.96126    0.07592  12.662  < 2e-16 ***
## category_code_LT01_5_count   0.92590    0.06242  14.832  < 2e-16 ***
## category_code_LT01_7_count   0.52601    0.15437   3.407  0.00071 ***
## category_code_LT01_12_count  0.19490    0.20551   0.948  0.34341    
## category_code_LT01_15_count  0.40474    0.75306   0.537  0.59119    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6175 
## F-statistic: 161.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 0.618188153833179 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0339 -0.7801  0.0249  0.8740  4.0330 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00885    0.08743 114.481  < 2e-16 ***
## category_code_LT01_4_count   0.96359    0.07475  12.890  < 2e-16 ***
## category_code_LT01_5_count   0.92355    0.06240  14.801  < 2e-16 ***
## category_code_LT01_7_count   0.52337    0.15419   3.394 0.000744 ***
## category_code_LT01_12_count  0.19321    0.20532   0.941 0.347168    
## category_code_LT01_16_count  1.25222    1.16807   1.072 0.284226    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6182 
## F-statistic: 161.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616662852213546 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0407 -0.7630 -0.0010  0.8408  4.0306 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01127    0.08766 114.203  < 2e-16 ***
## category_code_LT01_4_count   0.98075    0.07457  13.151  < 2e-16 ***
## category_code_LT01_5_count   0.92992    0.06250  14.878  < 2e-16 ***
## category_code_LT01_7_count   0.52110    0.15598   3.341 0.000899 ***
## category_code_LT01_13_count  0.04325    0.24662   0.175 0.860852    
## category_code_LT01_14_count  0.06773    0.33043   0.205 0.837685    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6205, Adjusted R-squared:  0.6167 
## F-statistic: 160.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616854360905638 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0410 -0.7516  0.0029  0.8388  4.0315 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01042    0.08756 114.322   <2e-16 ***
## category_code_LT01_4_count   0.97620    0.07447  13.109   <2e-16 ***
## category_code_LT01_5_count   0.93153    0.06218  14.981   <2e-16 ***
## category_code_LT01_7_count   0.52485    0.15558   3.374   0.0008 ***
## category_code_LT01_13_count  0.05063    0.24698   0.205   0.8377    
## category_code_LT01_15_count  0.40514    0.75499   0.537   0.5918    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.6169 
## F-statistic:   161 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617535267187884 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0393 -0.7543  0.0022  0.8384  4.0314 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01044    0.08749 114.424  < 2e-16 ***
## category_code_LT01_4_count   0.97831    0.07325  13.357  < 2e-16 ***
## category_code_LT01_5_count   0.92911    0.06215  14.949  < 2e-16 ***
## category_code_LT01_7_count   0.52210    0.15542   3.359 0.000842 ***
## category_code_LT01_13_count  0.05176    0.24647   0.210 0.833760    
## category_code_LT01_16_count  1.26222    1.16974   1.079 0.281089    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6175 
## F-statistic: 161.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616851659041435 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0411 -0.7564  0.0012  0.8521  4.0306 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01125    0.08764 114.233  < 2e-16 ***
## category_code_LT01_4_count   0.97535    0.07522  12.967  < 2e-16 ***
## category_code_LT01_5_count   0.93056    0.06248  14.894  < 2e-16 ***
## category_code_LT01_7_count   0.52647    0.15487   3.399  0.00073 ***
## category_code_LT01_14_count  0.06486    0.33036   0.196  0.84443    
## category_code_LT01_15_count  0.39398    0.75373   0.523  0.60142    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 492 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.6169 
## F-statistic:   161 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617551807365614 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0394 -0.7604  0.0037  0.8624  4.0304 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01148    0.08756 114.340  < 2e-16 ***
## category_code_LT01_4_count   0.97643    0.07416  13.166  < 2e-16 ***
## category_code_LT01_5_count   0.92777    0.06246  14.855  < 2e-16 ***
## category_code_LT01_7_count   0.52321    0.15468   3.382 0.000776 ***
## category_code_LT01_14_count  0.08448    0.33041   0.256 0.798297    
## category_code_LT01_16_count  1.26839    1.17041   1.084 0.279025    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 492 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6176 
## F-statistic: 161.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617740250062746 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0398 -0.7509  0.0045  0.8624  4.0314 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01046    0.08746 114.457  < 2e-16 ***
## category_code_LT01_4_count   0.97262    0.07395  13.152  < 2e-16 ***
## category_code_LT01_5_count   0.92975    0.06213  14.965  < 2e-16 ***
## category_code_LT01_7_count   0.52813    0.15431   3.423 0.000672 ***
## category_code_LT01_15_count  0.41790    0.75306   0.555 0.579193    
## category_code_LT01_16_count  1.27130    1.16917   1.087 0.277416    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 492 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.6177 
## F-statistic: 161.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 0.613619285674102 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0074 -0.7846 -0.0065  0.9059  3.9080 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97353    0.09146 109.045   <2e-16 ***
## category_code_LT01_4_count   1.04357    0.06797  15.353   <2e-16 ***
## category_code_LT01_5_count   0.93631    0.06323  14.808   <2e-16 ***
## category_code_LT01_8_count  -0.15783    0.27728  -0.569   0.5695    
## category_code_LT01_9_count   0.50997    0.22806   2.236   0.0258 *  
## category_code_LT01_10_count  0.14594    0.11392   1.281   0.2008    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 492 degrees of freedom
## Multiple R-squared:  0.6175, Adjusted R-squared:  0.6136 
## F-statistic: 158.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 0.624847088381565 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0311 -0.7680  0.0330  0.9373  3.7277 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00591    0.08675 115.339  < 2e-16 ***
## category_code_LT01_4_count   0.82647    0.08739   9.457  < 2e-16 ***
## category_code_LT01_5_count   0.92376    0.06239  14.807  < 2e-16 ***
## category_code_LT01_8_count  -0.12521    0.27325  -0.458   0.6470    
## category_code_LT01_9_count   0.45393    0.22402   2.026   0.0433 *  
## category_code_LT01_11_count  0.44480    0.10979   4.052 5.91e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6248 
## F-statistic: 166.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 0.613055260342051 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0341 -0.7933  0.0124  0.9386  4.0382 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00371    0.08812 113.524   <2e-16 ***
## category_code_LT01_4_count   1.04164    0.06932  15.026   <2e-16 ***
## category_code_LT01_5_count   0.93124    0.06355  14.654   <2e-16 ***
## category_code_LT01_8_count  -0.16074    0.27761  -0.579   0.5629    
## category_code_LT01_9_count   0.54285    0.22636   2.398   0.0168 *  
## category_code_LT01_12_count  0.19857    0.20686   0.960   0.3376    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6169, Adjusted R-squared:  0.6131 
## F-statistic: 158.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 0.612699914429394 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0377 -0.7942  0.0170  0.9307  4.0372 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00465    0.08815 113.496   <2e-16 ***
## category_code_LT01_4_count   1.04933    0.06842  15.337   <2e-16 ***
## category_code_LT01_5_count   0.93512    0.06336  14.760   <2e-16 ***
## category_code_LT01_8_count  -0.14047    0.27799  -0.505   0.6136    
## category_code_LT01_9_count   0.55641    0.22674   2.454   0.0145 *  
## category_code_LT01_13_count  0.16912    0.24689   0.685   0.4937    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 492 degrees of freedom
## Multiple R-squared:  0.6166, Adjusted R-squared:  0.6127 
## F-statistic: 158.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 0.612393194899172 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0395 -0.7960  0.0152  0.9077  4.0355 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00639    0.08827 113.364   <2e-16 ***
## category_code_LT01_4_count   1.05441    0.06883  15.320   <2e-16 ***
## category_code_LT01_5_count   0.93516    0.06362  14.700   <2e-16 ***
## category_code_LT01_8_count  -0.15208    0.27769  -0.548    0.584    
## category_code_LT01_9_count   0.54348    0.22702   2.394    0.017 *  
## category_code_LT01_14_count  0.09371    0.33224   0.282    0.778    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 492 degrees of freedom
## Multiple R-squared:  0.6163, Adjusted R-squared:  0.6124 
## F-statistic:   158 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 0.61251239113514 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0397 -0.7948  0.0126  0.9268  4.0367 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00521    0.08817 113.481   <2e-16 ***
## category_code_LT01_4_count   1.05259    0.06826  15.420   <2e-16 ***
## category_code_LT01_5_count   0.93726    0.06333  14.800   <2e-16 ***
## category_code_LT01_8_count  -0.15270    0.27764  -0.550   0.5826    
## category_code_LT01_9_count   0.54954    0.22648   2.426   0.0156 *  
## category_code_LT01_15_count  0.36417    0.75782   0.481   0.6311    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 492 degrees of freedom
## Multiple R-squared:  0.6164, Adjusted R-squared:  0.6125 
## F-statistic: 158.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 0.613107870468456 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0389 -0.7951  0.0045  0.9379  4.0364 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00551    0.08810 113.571   <2e-16 ***
## category_code_LT01_4_count   1.05486    0.06709  15.724   <2e-16 ***
## category_code_LT01_5_count   0.93565    0.06328  14.785   <2e-16 ***
## category_code_LT01_8_count  -0.16453    0.27774  -0.592    0.554    
## category_code_LT01_9_count   0.53763    0.22651   2.374    0.018 *  
## category_code_LT01_16_count  1.17173    1.17850   0.994    0.321    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.617,  Adjusted R-squared:  0.6131 
## F-statistic: 158.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 0.623019852502819 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0113 -0.7476  0.0348  0.9326  3.5839 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98047    0.09036 110.457  < 2e-16 ***
## category_code_LT01_4_count   0.83671    0.08741   9.572  < 2e-16 ***
## category_code_LT01_5_count   0.93187    0.06238  14.938  < 2e-16 ***
## category_code_LT01_8_count  -0.11400    0.27381  -0.416    0.677    
## category_code_LT01_10_count  0.14589    0.11186   1.304    0.193    
## category_code_LT01_11_count  0.45767    0.10974   4.171 3.59e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 492 degrees of freedom
## Multiple R-squared:  0.6268, Adjusted R-squared:  0.623 
## F-statistic: 165.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 0.610381644564625 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0111 -0.7797  0.0244  0.9262  3.8776 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97356    0.09185 108.590   <2e-16 ***
## category_code_LT01_4_count   1.06270    0.06867  15.476   <2e-16 ***
## category_code_LT01_5_count   0.94160    0.06359  14.808   <2e-16 ***
## category_code_LT01_8_count  -0.14781    0.27848  -0.531    0.596    
## category_code_LT01_10_count  0.17358    0.11358   1.528    0.127    
## category_code_LT01_12_count  0.19385    0.20779   0.933    0.351    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6104 
## F-statistic: 156.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 0.60988826676679 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.7774  0.0181  0.9307  3.8733 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97402    0.09190 108.528   <2e-16 ***
## category_code_LT01_4_count   1.07299    0.06756  15.883   <2e-16 ***
## category_code_LT01_5_count   0.94603    0.06339  14.924   <2e-16 ***
## category_code_LT01_8_count  -0.13041    0.27895  -0.468    0.640    
## category_code_LT01_10_count  0.17712    0.11356   1.560    0.119    
## category_code_LT01_13_count  0.12304    0.24754   0.497    0.619    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6138, Adjusted R-squared:  0.6099 
## F-statistic: 156.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 0.609702004800266 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0159 -0.7858  0.0202  0.9242  3.8733 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97500    0.09239 107.960   <2e-16 ***
## category_code_LT01_4_count   1.07762    0.06791  15.869   <2e-16 ***
## category_code_LT01_5_count   0.94645    0.06368  14.863   <2e-16 ***
## category_code_LT01_8_count  -0.13882    0.27856  -0.498    0.618    
## category_code_LT01_10_count  0.17623    0.11623   1.516    0.130    
## category_code_LT01_14_count  0.03750    0.34052   0.110    0.912    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6136, Adjusted R-squared:  0.6097 
## F-statistic: 156.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 0.609769013655282 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0162 -0.7827  0.0200  0.9262  3.8739 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97459    0.09194 108.492   <2e-16 ***
## category_code_LT01_4_count   1.07558    0.06741  15.955   <2e-16 ***
## category_code_LT01_5_count   0.94745    0.06337  14.952   <2e-16 ***
## category_code_LT01_8_count  -0.13933    0.27853  -0.500    0.617    
## category_code_LT01_10_count  0.17602    0.11392   1.545    0.123    
## category_code_LT01_15_count  0.23719    0.76308   0.311    0.756    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6137, Adjusted R-squared:  0.6098 
## F-statistic: 156.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 0.610520160786075 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0157 -0.7863  0.0230  0.9348  3.8763 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97532    0.09184 108.619   <2e-16 ***
## category_code_LT01_4_count   1.07499    0.06647  16.172   <2e-16 ***
## category_code_LT01_5_count   0.94572    0.06331  14.937   <2e-16 ***
## category_code_LT01_8_count  -0.15248    0.27859  -0.547    0.584    
## category_code_LT01_10_count  0.17322    0.11355   1.526    0.128    
## category_code_LT01_16_count  1.20937    1.18267   1.023    0.307    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6105 
## F-statistic: 156.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 0.621733412919486 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0451 -0.7425  0.0232  0.9111  3.7014 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01302    0.08706 115.011  < 2e-16 ***
## category_code_LT01_4_count   0.84972    0.08704   9.763  < 2e-16 ***
## category_code_LT01_5_count   0.93365    0.06269  14.894  < 2e-16 ***
## category_code_LT01_8_count  -0.10341    0.27446  -0.377    0.706    
## category_code_LT01_11_count  0.47246    0.11402   4.144 4.02e-05 ***
## category_code_LT01_12_count -0.03155    0.21262  -0.148    0.882    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.6217 
## F-statistic: 164.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 0.621789173564034 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0436 -0.7338  0.0261  0.9052  3.7064 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01255    0.08704 115.032  < 2e-16 ***
## category_code_LT01_4_count   0.84658    0.08750   9.675  < 2e-16 ***
## category_code_LT01_5_count   0.93228    0.06251  14.914  < 2e-16 ***
## category_code_LT01_8_count  -0.10043    0.27462  -0.366    0.715    
## category_code_LT01_11_count  0.46584    0.10983   4.242 2.65e-05 ***
## category_code_LT01_13_count  0.07504    0.24403   0.307    0.759    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6256, Adjusted R-squared:  0.6218 
## F-statistic: 164.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 0.621802920298579 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0441 -0.7345  0.0279  0.9147  3.7043 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01399    0.08711 114.954  < 2e-16 ***
## category_code_LT01_4_count   0.84441    0.08828   9.565  < 2e-16 ***
## category_code_LT01_5_count   0.93083    0.06278  14.826  < 2e-16 ***
## category_code_LT01_8_count  -0.10661    0.27420  -0.389    0.698    
## category_code_LT01_11_count  0.46681    0.10968   4.256 2.49e-05 ***
## category_code_LT01_14_count  0.10983    0.32753   0.335    0.738    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6256, Adjusted R-squared:  0.6218 
## F-statistic: 164.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 0.621737277353436 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0444 -0.7350  0.0245  0.9133  3.7057 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01276    0.08704 115.031  < 2e-16 ***
## category_code_LT01_4_count   0.84801    0.08744   9.698  < 2e-16 ***
## category_code_LT01_5_count   0.93309    0.06249  14.931  < 2e-16 ***
## category_code_LT01_8_count  -0.10578    0.27422  -0.386    0.700    
## category_code_LT01_11_count  0.46662    0.10989   4.246  2.6e-05 ***
## category_code_LT01_15_count  0.12338    0.75033   0.164    0.869    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.6217 
## F-statistic: 164.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 0.622390743083028 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0435 -0.7338  0.0268  0.9097  3.7078 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01285    0.08697 115.131  < 2e-16 ***
## category_code_LT01_4_count   0.84734    0.08697   9.743  < 2e-16 ***
## category_code_LT01_5_count   0.93172    0.06244  14.921  < 2e-16 ***
## category_code_LT01_8_count  -0.11832    0.27432  -0.431    0.666    
## category_code_LT01_11_count  0.46349    0.10965   4.227 2.82e-05 ***
## category_code_LT01_16_count  1.09111    1.16412   0.937    0.349    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 492 degrees of freedom
## Multiple R-squared:  0.6262, Adjusted R-squared:  0.6224 
## F-statistic: 164.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 0.608743804938998 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0491 -0.8010  0.0077  0.9341  4.0304 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01153    0.08855 113.066   <2e-16 ***
## category_code_LT01_4_count   1.07655    0.06864  15.683   <2e-16 ***
## category_code_LT01_5_count   0.94170    0.06375  14.772   <2e-16 ***
## category_code_LT01_8_count  -0.13026    0.27949  -0.466    0.641    
## category_code_LT01_12_count  0.20661    0.20806   0.993    0.321    
## category_code_LT01_13_count  0.12795    0.24790   0.516    0.606    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 492 degrees of freedom
## Multiple R-squared:  0.6127, Adjusted R-squared:  0.6087 
## F-statistic: 155.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 0.608640736480718 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0501 -0.8023  0.0038  0.9262  4.0286 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01330    0.08864 112.968   <2e-16 ***
## category_code_LT01_4_count   1.07717    0.06930  15.545   <2e-16 ***
## category_code_LT01_5_count   0.94057    0.06400  14.696   <2e-16 ***
## category_code_LT01_8_count  -0.13997    0.27906  -0.502    0.616    
## category_code_LT01_12_count  0.20420    0.20857   0.979    0.328    
## category_code_LT01_14_count  0.12352    0.33401   0.370    0.712    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 492 degrees of freedom
## Multiple R-squared:  0.6126, Adjusted R-squared:  0.6086 
## F-statistic: 155.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 0.608696115679377 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0504 -0.8014  0.0079  0.9402  4.0301 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01182    0.08855 113.066   <2e-16 ***
## category_code_LT01_4_count   1.07701    0.06877  15.662   <2e-16 ***
## category_code_LT01_5_count   0.94315    0.06373  14.800   <2e-16 ***
## category_code_LT01_8_count  -0.14025    0.27904  -0.503    0.615    
## category_code_LT01_12_count  0.21127    0.20798   1.016    0.310    
## category_code_LT01_15_count  0.34597    0.76152   0.454    0.650    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 492 degrees of freedom
## Multiple R-squared:  0.6126, Adjusted R-squared:  0.6087 
## F-statistic: 155.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 0.609489456794958 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0492 -0.8015  0.0035  0.9401  4.0299 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01196    0.08846 113.182   <2e-16 ***
## category_code_LT01_4_count   1.07765    0.06763  15.934   <2e-16 ***
## category_code_LT01_5_count   0.94118    0.06367  14.782   <2e-16 ***
## category_code_LT01_8_count  -0.15411    0.27909  -0.552    0.581    
## category_code_LT01_12_count  0.21008    0.20775   1.011    0.312    
## category_code_LT01_16_count  1.29909    1.18278   1.098    0.273    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6134, Adjusted R-squared:  0.6095 
## F-statistic: 156.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 0.608117210747575 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0546 -0.7850 -0.0077  0.9213  4.0270 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01487    0.08868 112.935   <2e-16 ***
## category_code_LT01_4_count   1.08690    0.06841  15.887   <2e-16 ***
## category_code_LT01_5_count   0.94474    0.06385  14.797   <2e-16 ***
## category_code_LT01_8_count  -0.12134    0.27953  -0.434    0.664    
## category_code_LT01_13_count  0.13581    0.24797   0.548    0.584    
## category_code_LT01_14_count  0.14825    0.33328   0.445    0.657    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.41 on 492 degrees of freedom
## Multiple R-squared:  0.6121, Adjusted R-squared:  0.6081 
## F-statistic: 155.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 0.608139398592454 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0551 -0.7903 -0.0072  0.9368  4.0287 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01314    0.08860 113.018   <2e-16 ***
## category_code_LT01_4_count   1.08796    0.06767  16.078   <2e-16 ***
## category_code_LT01_5_count   0.94796    0.06353  14.922   <2e-16 ***
## category_code_LT01_8_count  -0.12056    0.27950  -0.431    0.666    
## category_code_LT01_13_count  0.14301    0.24843   0.576    0.565    
## category_code_LT01_15_count  0.36272    0.76343   0.475    0.635    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.41 on 492 degrees of freedom
## Multiple R-squared:  0.6121, Adjusted R-squared:  0.6081 
## F-statistic: 155.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 0.608946814369058 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0538 -0.7878 -0.0046  0.9370  4.0286 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01328    0.08851 113.136   <2e-16 ***
## category_code_LT01_4_count   1.08863    0.06643  16.388   <2e-16 ***
## category_code_LT01_5_count   0.94590    0.06348  14.902   <2e-16 ***
## category_code_LT01_8_count  -0.13457    0.27953  -0.481    0.630    
## category_code_LT01_13_count  0.14416    0.24782   0.582    0.561    
## category_code_LT01_16_count  1.31969    1.18415   1.114    0.266    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 492 degrees of freedom
## Multiple R-squared:  0.6129, Adjusted R-squared:  0.6089 
## F-statistic: 155.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 0.608029407782607 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0561 -0.8031 -0.0090  0.9350  4.0267 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01520    0.08868 112.930   <2e-16 ***
## category_code_LT01_4_count   1.08851    0.06835  15.925   <2e-16 ***
## category_code_LT01_5_count   0.94642    0.06382  14.830   <2e-16 ***
## category_code_LT01_8_count  -0.13153    0.27911  -0.471    0.638    
## category_code_LT01_14_count  0.14653    0.33334   0.440    0.660    
## category_code_LT01_15_count  0.33196    0.76215   0.436    0.663    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.41 on 492 degrees of freedom
## Multiple R-squared:  0.612,  Adjusted R-squared:  0.608 
## F-statistic: 155.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 0.608875971065954 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0548 -0.8018 -0.0065  0.9350  4.0263 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01555    0.08859 113.056   <2e-16 ***
## category_code_LT01_4_count   1.08768    0.06735  16.150   <2e-16 ***
## category_code_LT01_5_count   0.94402    0.06377  14.804   <2e-16 ***
## category_code_LT01_8_count  -0.14608    0.27916  -0.523    0.601    
## category_code_LT01_14_count  0.16641    0.33336   0.499    0.618    
## category_code_LT01_16_count  1.32766    1.18512   1.120    0.263    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 492 degrees of freedom
## Multiple R-squared:  0.6128, Adjusted R-squared:  0.6089 
## F-statistic: 155.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 0.608854526763068 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0554 -0.7932 -0.0093  0.9539  4.0282 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01365    0.08851 113.131   <2e-16 ***
## category_code_LT01_4_count   1.09016    0.06640  16.418   <2e-16 ***
## category_code_LT01_5_count   0.94766    0.06345  14.936   <2e-16 ***
## category_code_LT01_8_count  -0.14537    0.27915  -0.521    0.603    
## category_code_LT01_15_count  0.35901    0.76159   0.471    0.638    
## category_code_LT01_16_count  1.31414    1.18419   1.110    0.268    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 492 degrees of freedom
## Multiple R-squared:  0.6128, Adjusted R-squared:  0.6089 
## F-statistic: 155.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.625537443678239 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0007 -0.7618  0.0384  0.9211  3.6282 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97881    0.09003 110.839  < 2e-16 ***
## category_code_LT01_4_count   0.81630    0.08768   9.310  < 2e-16 ***
## category_code_LT01_5_count   0.91905    0.06164  14.911  < 2e-16 ***
## category_code_LT01_9_count   0.42065    0.22542   1.866   0.0626 .  
## category_code_LT01_10_count  0.11873    0.11232   1.057   0.2910    
## category_code_LT01_11_count  0.43926    0.10984   3.999 7.33e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 492 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6255 
## F-statistic:   167 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 0.613971802755224 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9983 -0.7881  0.0031  0.9318  3.9165 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97183    0.09140 109.106   <2e-16 ***
## category_code_LT01_4_count   1.02765    0.07011  14.657   <2e-16 ***
## category_code_LT01_5_count   0.92556    0.06281  14.736   <2e-16 ***
## category_code_LT01_9_count   0.50237    0.22788   2.205   0.0279 *  
## category_code_LT01_10_count  0.13980    0.11399   1.226   0.2206    
## category_code_LT01_12_count  0.18182    0.20673   0.880   0.3795    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.399 on 492 degrees of freedom
## Multiple R-squared:  0.6179, Adjusted R-squared:  0.614 
## F-statistic: 159.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 0.61371280288695 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0017 -0.7692 -0.0080  0.9191  3.9138 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97243    0.09143 109.077   <2e-16 ***
## category_code_LT01_4_count   1.03407    0.06924  14.935   <2e-16 ***
## category_code_LT01_5_count   0.92966    0.06256  14.861   <2e-16 ***
## category_code_LT01_9_count   0.51528    0.22835   2.257   0.0245 *  
## category_code_LT01_10_count  0.14172    0.11398   1.243   0.2143    
## category_code_LT01_13_count  0.16402    0.24637   0.666   0.5059    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 492 degrees of freedom
## Multiple R-squared:  0.6176, Adjusted R-squared:  0.6137 
## F-statistic: 158.9 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 0.613364952484745 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0025 -0.7812 -0.0045  0.9143  3.9108 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.972396   0.091934 108.473   <2e-16 ***
## category_code_LT01_4_count  1.042748   0.069301  15.047   <2e-16 ***
## category_code_LT01_5_count  0.930907   0.062857  14.810   <2e-16 ***
## category_code_LT01_9_count  0.505812   0.228227   2.216   0.0271 *  
## category_code_LT01_10_count 0.144423   0.116483   1.240   0.2156    
## category_code_LT01_14_count 0.004012   0.339208   0.012   0.9906    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 492 degrees of freedom
## Multiple R-squared:  0.6173, Adjusted R-squared:  0.6134 
## F-statistic: 158.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 0.61347009080646 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0034 -0.7848  0.0021  0.9133  3.9139 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97301    0.09148 109.024   <2e-16 ***
## category_code_LT01_4_count   1.03853    0.06902  15.046   <2e-16 ***
## category_code_LT01_5_count   0.93126    0.06255  14.888   <2e-16 ***
## category_code_LT01_9_count   0.50812    0.22807   2.228   0.0263 *  
## category_code_LT01_10_count  0.14109    0.11435   1.234   0.2179    
## category_code_LT01_15_count  0.27806    0.75969   0.366   0.7145    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 492 degrees of freedom
## Multiple R-squared:  0.6174, Adjusted R-squared:  0.6135 
## F-statistic: 158.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 0.614016659177626 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0025 -0.7751 -0.0073  0.9233  3.9146 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97340    0.09140 109.121   <2e-16 ***
## category_code_LT01_4_count   1.03972    0.06802  15.286   <2e-16 ***
## category_code_LT01_5_count   0.92949    0.06252  14.866   <2e-16 ***
## category_code_LT01_9_count   0.49744    0.22802   2.182   0.0296 *  
## category_code_LT01_10_count  0.14004    0.11396   1.229   0.2197    
## category_code_LT01_16_count  1.07277    1.17692   0.912   0.3625    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.399 on 492 degrees of freedom
## Multiple R-squared:  0.6179, Adjusted R-squared:  0.614 
## F-statistic: 159.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.624705982850419 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0278 -0.7597  0.0344  0.9397  3.7244 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00500    0.08675 115.334  < 2e-16 ***
## category_code_LT01_4_count   0.82556    0.08739   9.447  < 2e-16 ***
## category_code_LT01_5_count   0.92036    0.06195  14.858  < 2e-16 ***
## category_code_LT01_9_count   0.45008    0.22392   2.010    0.045 *  
## category_code_LT01_11_count  0.45088    0.11409   3.952 8.88e-05 ***
## category_code_LT01_12_count -0.03340    0.21158  -0.158    0.875    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.6247 
## F-statistic: 166.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.62484733115233 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0260 -0.7519  0.0412  0.9170  3.7307 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00435    0.08672 115.369  < 2e-16 ***
## category_code_LT01_4_count   0.82075    0.08789   9.338  < 2e-16 ***
## category_code_LT01_5_count   0.91868    0.06172  14.886  < 2e-16 ***
## category_code_LT01_9_count   0.45675    0.22433   2.036   0.0423 *  
## category_code_LT01_11_count  0.44265    0.11000   4.024 6.62e-05 ***
## category_code_LT01_13_count  0.11150    0.24314   0.459   0.6467    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6248 
## F-statistic: 166.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.624716695354764 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0269 -0.7542  0.0403  0.9444  3.7276 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00546    0.08681 115.254  < 2e-16 ***
## category_code_LT01_4_count   0.82242    0.08852   9.291  < 2e-16 ***
## category_code_LT01_5_count   0.91832    0.06199  14.814  < 2e-16 ***
## category_code_LT01_9_count   0.44727    0.22441   1.993   0.0468 *  
## category_code_LT01_11_count  0.44554    0.10980   4.058 5.76e-05 ***
## category_code_LT01_14_count  0.06454    0.32696   0.197   0.8436    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.6247 
## F-statistic: 166.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.624718878394859 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0270 -0.7707  0.0406  0.9361  3.7292 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00467    0.08673 115.358  < 2e-16 ***
## category_code_LT01_4_count   0.82341    0.08781   9.377  < 2e-16 ***
## category_code_LT01_5_count   0.91969    0.06171  14.904  < 2e-16 ***
## category_code_LT01_9_count   0.45123    0.22397   2.015   0.0445 *  
## category_code_LT01_11_count  0.44444    0.11003   4.039 6.22e-05 ***
## category_code_LT01_15_count  0.15287    0.74749   0.205   0.8380    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 492 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.6247 
## F-statistic: 166.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.625216855024373 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0261 -0.7549  0.0458  0.9358  3.7303 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00479    0.08667 115.436  < 2e-16 ***
## category_code_LT01_4_count   0.82366    0.08733   9.432  < 2e-16 ***
## category_code_LT01_5_count   0.91822    0.06168  14.887  < 2e-16 ***
## category_code_LT01_9_count   0.44217    0.22398   1.974   0.0489 *  
## category_code_LT01_11_count  0.44263    0.10978   4.032  6.4e-05 ***
## category_code_LT01_16_count  0.96690    1.15932   0.834   0.4047    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 492 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6252 
## F-statistic: 166.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 0.613161538105201 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0275 -0.7913  0.0293  0.9426  4.0402 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00172    0.08807 113.563   <2e-16 ***
## category_code_LT01_4_count   1.03216    0.07055  14.630   <2e-16 ***
## category_code_LT01_5_count   0.92469    0.06290  14.701   <2e-16 ***
## category_code_LT01_9_count   0.54748    0.22658   2.416    0.016 *  
## category_code_LT01_12_count  0.18984    0.20679   0.918    0.359    
## category_code_LT01_13_count  0.16907    0.24648   0.686    0.493    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6171, Adjusted R-squared:  0.6132 
## F-statistic: 158.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 0.6128250191633 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0289 -0.7926  0.0230  0.9463  4.0388 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00304    0.08820 113.413   <2e-16 ***
## category_code_LT01_4_count   1.03826    0.07080  14.664   <2e-16 ***
## category_code_LT01_5_count   0.92476    0.06316  14.642   <2e-16 ***
## category_code_LT01_9_count   0.53537    0.22681   2.360   0.0186 *  
## category_code_LT01_12_count  0.19106    0.20736   0.921   0.3573    
## category_code_LT01_14_count  0.06862    0.33295   0.206   0.8368    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6167, Adjusted R-squared:  0.6128 
## F-statistic: 158.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 0.612977375297598 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0290 -0.7917  0.0246  0.9406  4.0398 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00210    0.08809 113.543   <2e-16 ***
## category_code_LT01_4_count   1.03480    0.07057  14.664   <2e-16 ***
## category_code_LT01_5_count   0.92625    0.06289  14.727   <2e-16 ***
## category_code_LT01_9_count   0.54014    0.22628   2.387   0.0174 *  
## category_code_LT01_12_count  0.19549    0.20676   0.945   0.3449    
## category_code_LT01_15_count  0.36806    0.75737   0.486   0.6272    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6169, Adjusted R-squared:  0.613 
## F-statistic: 158.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 0.613525630951027 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0279 -0.7919  0.0195  0.9478  4.0396 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00231    0.08803 113.627   <2e-16 ***
## category_code_LT01_4_count   1.03732    0.06939  14.949   <2e-16 ***
## category_code_LT01_5_count   0.92433    0.06287  14.703   <2e-16 ***
## category_code_LT01_9_count   0.52823    0.22635   2.334    0.020 *  
## category_code_LT01_12_count  0.19415    0.20660   0.940    0.348    
## category_code_LT01_16_count  1.13727    1.17647   0.967    0.334    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 492 degrees of freedom
## Multiple R-squared:  0.6174, Adjusted R-squared:  0.6135 
## F-statistic: 158.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 0.612557763954034 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0329 -0.7939  0.0273  0.9101  4.0375 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00435    0.08821 113.414   <2e-16 ***
## category_code_LT01_4_count   1.04397    0.07015  14.881   <2e-16 ***
## category_code_LT01_5_count   0.92864    0.06295  14.752   <2e-16 ***
## category_code_LT01_9_count   0.54861    0.22722   2.414   0.0161 *  
## category_code_LT01_13_count  0.17591    0.24655   0.713   0.4759    
## category_code_LT01_14_count  0.09080    0.33214   0.273   0.7847    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 492 degrees of freedom
## Multiple R-squared:  0.6165, Adjusted R-squared:  0.6126 
## F-statistic: 158.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 0.612711786123321 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0331 -0.7927  0.0258  0.9285  4.0387 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00316    0.08811 113.534   <2e-16 ***
## category_code_LT01_4_count   1.04103    0.06977  14.920   <2e-16 ***
## category_code_LT01_5_count   0.93063    0.06264  14.857   <2e-16 ***
## category_code_LT01_9_count   0.55509    0.22667   2.449   0.0147 *  
## category_code_LT01_13_count  0.18416    0.24699   0.746   0.4563    
## category_code_LT01_15_count  0.39475    0.75908   0.520   0.6033    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 492 degrees of freedom
## Multiple R-squared:  0.6166, Adjusted R-squared:  0.6127 
## F-statistic: 158.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 0.613267887009262 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0319 -0.7929  0.0164  0.9398  4.0385 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00336    0.08804 113.618   <2e-16 ***
## category_code_LT01_4_count   1.04383    0.06848  15.243   <2e-16 ***
## category_code_LT01_5_count   0.92861    0.06262  14.830   <2e-16 ***
## category_code_LT01_9_count   0.54275    0.22670   2.394    0.017 *  
## category_code_LT01_13_count  0.18354    0.24644   0.745    0.457    
## category_code_LT01_16_count  1.16457    1.17742   0.989    0.323    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6172, Adjusted R-squared:  0.6133 
## F-statistic: 158.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 0.612331308540368 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0346 -0.7944  0.0244  0.9089  4.0371 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00479    0.08823 113.390   <2e-16 ***
## category_code_LT01_4_count   1.04774    0.07000  14.968   <2e-16 ***
## category_code_LT01_5_count   0.93044    0.06294  14.782   <2e-16 ***
## category_code_LT01_9_count   0.54107    0.22695   2.384   0.0175 *  
## category_code_LT01_14_count  0.08948    0.33227   0.269   0.7878    
## category_code_LT01_15_count  0.35661    0.75801   0.470   0.6382    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 492 degrees of freedom
## Multiple R-squared:  0.6162, Adjusted R-squared:  0.6123 
## F-statistic:   158 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 0.61291530238593 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0334 -0.7948  0.0153  0.9167  4.0367 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00520    0.08817 113.480   <2e-16 ***
## category_code_LT01_4_count   1.04899    0.06894  15.216   <2e-16 ***
## category_code_LT01_5_count   0.92811    0.06292  14.750   <2e-16 ***
## category_code_LT01_9_count   0.52812    0.22704   2.326   0.0204 *  
## category_code_LT01_14_count  0.10824    0.33243   0.326   0.7449    
## category_code_LT01_16_count  1.15751    1.17896   0.982   0.3267    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6168, Adjusted R-squared:  0.6129 
## F-statistic: 158.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 0.61302839083483 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0337 -0.7934  0.0134  0.9316  4.0380 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00384    0.08807 113.593   <2e-16 ***
## category_code_LT01_4_count   1.04762    0.06835  15.328   <2e-16 ***
## category_code_LT01_5_count   0.93048    0.06261  14.862   <2e-16 ***
## category_code_LT01_9_count   0.53495    0.22645   2.362   0.0185 *  
## category_code_LT01_15_count  0.37863    0.75753   0.500   0.6174    
## category_code_LT01_16_count  1.15320    1.17763   0.979   0.3279    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 492 degrees of freedom
## Multiple R-squared:  0.6169, Adjusted R-squared:  0.613 
## F-statistic: 158.5 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.622920607585906 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0086 -0.7510  0.0346  0.9337  3.5798 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97979    0.09035 110.459  < 2e-16 ***
## category_code_LT01_4_count   0.83587    0.08739   9.565  < 2e-16 ***
## category_code_LT01_5_count   0.92906    0.06191  15.008  < 2e-16 ***
## category_code_LT01_10_count  0.14553    0.11190   1.301    0.194    
## category_code_LT01_11_count  0.46511    0.11398   4.081 5.24e-05 ***
## category_code_LT01_12_count -0.04441    0.21220  -0.209    0.834    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 492 degrees of freedom
## Multiple R-squared:  0.6267, Adjusted R-squared:  0.6229 
## F-statistic: 165.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.62295314904572 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0074 -0.7397  0.0409  0.9131  3.5876 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97962    0.09034 110.468  < 2e-16 ***
## category_code_LT01_4_count   0.83293    0.08781   9.485  < 2e-16 ***
## category_code_LT01_5_count   0.92750    0.06168  15.037  < 2e-16 ***
## category_code_LT01_10_count  0.14384    0.11188   1.286    0.199    
## category_code_LT01_11_count  0.45679    0.10991   4.156 3.82e-05 ***
## category_code_LT01_13_count  0.07148    0.24335   0.294    0.769    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 492 degrees of freedom
## Multiple R-squared:  0.6267, Adjusted R-squared:  0.623 
## F-statistic: 165.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.622889359103285 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0079 -0.7410  0.0372  0.9340  3.5864 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98008    0.09080 109.907  < 2e-16 ***
## category_code_LT01_4_count   0.83478    0.08837   9.446  < 2e-16 ***
## category_code_LT01_5_count   0.92758    0.06198  14.965  < 2e-16 ***
## category_code_LT01_10_count  0.14340    0.11448   1.253    0.211    
## category_code_LT01_11_count  0.45858    0.10974   4.179 3.47e-05 ***
## category_code_LT01_14_count  0.01844    0.33473   0.055    0.956    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 492 degrees of freedom
## Multiple R-squared:  0.6267, Adjusted R-squared:  0.6229 
## F-statistic: 165.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.622889522654358 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0078 -0.7422  0.0368  0.9342  3.5861 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97969    0.09037 110.437  < 2e-16 ***
## category_code_LT01_4_count   0.83505    0.08773   9.518  < 2e-16 ***
## category_code_LT01_5_count   0.92799    0.06168  15.045  < 2e-16 ***
## category_code_LT01_10_count  0.14423    0.11220   1.286    0.199    
## category_code_LT01_11_count  0.45827    0.10994   4.169 3.62e-05 ***
## category_code_LT01_15_count  0.04284    0.75151   0.057    0.955    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 492 degrees of freedom
## Multiple R-squared:  0.6267, Adjusted R-squared:  0.6229 
## F-statistic: 165.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.623448752525444 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0076 -0.7344  0.0425  0.9122  3.5919 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98055    0.09029 110.543  < 2e-16 ***
## category_code_LT01_4_count   0.83387    0.08733   9.548  < 2e-16 ***
## category_code_LT01_5_count   0.92647    0.06165  15.029  < 2e-16 ***
## category_code_LT01_10_count  0.14015    0.11189   1.253    0.211    
## category_code_LT01_11_count  0.45511    0.10973   4.148 3.96e-05 ***
## category_code_LT01_16_count  0.99575    1.16230   0.857    0.392    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 492 degrees of freedom
## Multiple R-squared:  0.6272, Adjusted R-squared:  0.6234 
## F-statistic: 165.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 0.610356643764649 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0061 -0.7731  0.0236  0.9202  3.8820 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97252    0.09182 108.606   <2e-16 ***
## category_code_LT01_4_count   1.05624    0.06967  15.160   <2e-16 ***
## category_code_LT01_5_count   0.93589    0.06292  14.875   <2e-16 ***
## category_code_LT01_10_count  0.17059    0.11361   1.502    0.134    
## category_code_LT01_12_count  0.18699    0.20774   0.900    0.368    
## category_code_LT01_13_count  0.12357    0.24707   0.500    0.617    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6104 
## F-statistic: 156.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 0.610160120780359 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0067 -0.7740  0.0183  0.9286  3.8810 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97281    0.09232 108.025   <2e-16 ***
## category_code_LT01_4_count   1.06158    0.06990  15.187   <2e-16 ***
## category_code_LT01_5_count   0.93638    0.06320  14.816   <2e-16 ***
## category_code_LT01_10_count  0.17120    0.11622   1.473    0.141    
## category_code_LT01_12_count  0.18929    0.20817   0.909    0.364    
## category_code_LT01_14_count  0.01521    0.34106   0.045    0.964    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.6102 
## F-statistic: 156.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 0.61024069216197 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0073 -0.7741  0.0200  0.9331  3.8830 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97303    0.09186 108.571   <2e-16 ***
## category_code_LT01_4_count   1.05832    0.06970  15.185   <2e-16 ***
## category_code_LT01_5_count   0.93690    0.06292  14.892   <2e-16 ***
## category_code_LT01_10_count  0.16919    0.11398   1.484    0.138    
## category_code_LT01_12_count  0.19105    0.20772   0.920    0.358    
## category_code_LT01_15_count  0.24560    0.76270   0.322    0.748    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6102 
## F-statistic: 156.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 0.610946799522188 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0064 -0.7761  0.0080  0.9330  3.8853 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97360    0.09176 108.691   <2e-16 ***
## category_code_LT01_4_count   1.05798    0.06874  15.392   <2e-16 ***
## category_code_LT01_5_count   0.93478    0.06288  14.866   <2e-16 ***
## category_code_LT01_10_count  0.16656    0.11362   1.466    0.143    
## category_code_LT01_12_count  0.19012    0.20750   0.916    0.360    
## category_code_LT01_16_count  1.17873    1.18060   0.998    0.319    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 492 degrees of freedom
## Multiple R-squared:  0.6149, Adjusted R-squared:  0.6109 
## F-statistic: 157.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 0.609724477330306 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0110 -0.7694  0.0299  0.9150  3.8778 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97401    0.09236 107.986   <2e-16 ***
## category_code_LT01_4_count   1.07031    0.06902  15.508   <2e-16 ***
## category_code_LT01_5_count   0.94081    0.06299  14.937   <2e-16 ***
## category_code_LT01_10_count  0.17305    0.11627   1.488    0.137    
## category_code_LT01_13_count  0.13002    0.24718   0.526    0.599    
## category_code_LT01_14_count  0.03728    0.34051   0.109    0.913    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6137, Adjusted R-squared:  0.6097 
## F-statistic: 156.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 0.609807097144863 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0113 -0.7686  0.0301  0.9242  3.8788 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97367    0.09191 108.518   <2e-16 ***
## category_code_LT01_4_count   1.06764    0.06865  15.551   <2e-16 ***
## category_code_LT01_5_count   0.94178    0.06266  15.031   <2e-16 ***
## category_code_LT01_10_count  0.17245    0.11396   1.513    0.131    
## category_code_LT01_13_count  0.13527    0.24767   0.546    0.585    
## category_code_LT01_15_count  0.26060    0.76462   0.341    0.733    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6137, Adjusted R-squared:  0.6098 
## F-statistic: 156.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 0.61053188661524 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0104 -0.7696  0.0300  0.9239  3.8811 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97423    0.09181 108.641   <2e-16 ***
## category_code_LT01_4_count   1.06720    0.06761  15.784   <2e-16 ***
## category_code_LT01_5_count   0.93956    0.06262  15.003   <2e-16 ***
## category_code_LT01_10_count  0.16981    0.11359   1.495    0.136    
## category_code_LT01_13_count  0.13853    0.24707   0.561    0.575    
## category_code_LT01_16_count  1.20070    1.18195   1.016    0.310    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6105 
## F-statistic: 156.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 0.609579649297958 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0123 -0.7700  0.0297  0.9205  3.8784 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97448    0.09240 107.945   <2e-16 ***
## category_code_LT01_4_count   1.07327    0.06890  15.577   <2e-16 ***
## category_code_LT01_5_count   0.94198    0.06298  14.957   <2e-16 ***
## category_code_LT01_10_count  0.17207    0.11663   1.475    0.141    
## category_code_LT01_14_count  0.03650    0.34057   0.107    0.915    
## category_code_LT01_15_count  0.23410    0.76325   0.307    0.759    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6135, Adjusted R-squared:  0.6096 
## F-statistic: 156.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 0.610304753504323 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0117 -0.7772  0.0291  0.9201  3.8820 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97563    0.09231 108.064   <2e-16 ***
## category_code_LT01_4_count   1.07180    0.06802  15.756   <2e-16 ***
## category_code_LT01_5_count   0.93946    0.06296  14.923   <2e-16 ***
## category_code_LT01_10_count  0.16774    0.11634   1.442    0.150    
## category_code_LT01_14_count  0.05648    0.34086   0.166    0.868    
## category_code_LT01_16_count  1.18946    1.18373   1.005    0.315    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6103 
## F-statistic: 156.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 0.610373294598632 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0118 -0.7757  0.0281  0.9430  3.8818 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97476    0.09185 108.599   <2e-16 ***
## category_code_LT01_4_count   1.07023    0.06750  15.856   <2e-16 ***
## category_code_LT01_5_count   0.94082    0.06262  15.025   <2e-16 ***
## category_code_LT01_10_count  0.16865    0.11396   1.480    0.140    
## category_code_LT01_15_count  0.25758    0.76283   0.338    0.736    
## category_code_LT01_16_count  1.19011    1.18205   1.007    0.315    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 492 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6104 
## F-statistic: 156.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.621708500194027 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0411 -0.7317  0.0314  0.9053  3.7030 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01184    0.08702 115.046  < 2e-16 ***
## category_code_LT01_4_count   0.84558    0.08745   9.669  < 2e-16 ***
## category_code_LT01_5_count   0.92969    0.06202  14.991  < 2e-16 ***
## category_code_LT01_11_count  0.47177    0.11413   4.134  4.2e-05 ***
## category_code_LT01_12_count -0.03604    0.21244  -0.170    0.865    
## category_code_LT01_13_count  0.08066    0.24368   0.331    0.741    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.6217 
## F-statistic: 164.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.621714208828905 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0415 -0.7324  0.0316  0.9160  3.7004 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01330    0.08710 114.959  < 2e-16 ***
## category_code_LT01_4_count   0.84347    0.08825   9.557  < 2e-16 ***
## category_code_LT01_5_count   0.92812    0.06228  14.902  < 2e-16 ***
## category_code_LT01_11_count  0.47354    0.11397   4.155 3.84e-05 ***
## category_code_LT01_12_count -0.04026    0.21296  -0.189    0.850    
## category_code_LT01_14_count  0.11231    0.32837   0.342    0.732    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.6217 
## F-statistic: 164.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.621642568572665 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0417 -0.7325  0.0296  0.9160  3.7024 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01199    0.08703 115.039  < 2e-16 ***
## category_code_LT01_4_count   0.84722    0.08743   9.690  < 2e-16 ***
## category_code_LT01_5_count   0.93029    0.06201  15.002  < 2e-16 ***
## category_code_LT01_11_count  0.47252    0.11428   4.135 4.18e-05 ***
## category_code_LT01_12_count -0.03402    0.21255  -0.160    0.873    
## category_code_LT01_15_count  0.11582    0.75075   0.154    0.877    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6254, Adjusted R-squared:  0.6216 
## F-statistic: 164.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.622266649646136 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0404 -0.7312  0.0326  0.9149  3.7046 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01195    0.08696 115.134  < 2e-16 ***
## category_code_LT01_4_count   0.84637    0.08695   9.734  < 2e-16 ***
## category_code_LT01_5_count   0.92851    0.06198  14.981  < 2e-16 ***
## category_code_LT01_11_count  0.46939    0.11398   4.118 4.48e-05 ***
## category_code_LT01_12_count -0.03312    0.21227  -0.156    0.876    
## category_code_LT01_16_count  1.06368    1.16285   0.915    0.361    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 492 degrees of freedom
## Multiple R-squared:  0.6261, Adjusted R-squared:  0.6223 
## F-statistic: 164.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.62177026147877 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0399 -0.7310  0.0346  0.9145  3.7065 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01273    0.08707 114.992  < 2e-16 ***
## category_code_LT01_4_count   0.84028    0.08871   9.472  < 2e-16 ***
## category_code_LT01_5_count   0.92667    0.06209  14.924  < 2e-16 ***
## category_code_LT01_11_count  0.46551    0.10986   4.237  2.7e-05 ***
## category_code_LT01_13_count  0.08031    0.24364   0.330    0.742    
## category_code_LT01_14_count  0.10819    0.32751   0.330    0.741    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6256, Adjusted R-squared:  0.6218 
## F-statistic: 164.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.621711732508849 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0403 -0.7310  0.0325  0.9158  3.7080 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01150    0.08701 115.067  < 2e-16 ***
## category_code_LT01_4_count   0.84356    0.08792   9.595  < 2e-16 ***
## category_code_LT01_5_count   0.92893    0.06178  15.036  < 2e-16 ***
## category_code_LT01_11_count  0.46509    0.11010   4.224 2.86e-05 ***
## category_code_LT01_13_count  0.08302    0.24419   0.340    0.734    
## category_code_LT01_15_count  0.13658    0.75194   0.182    0.856    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.6217 
## F-statistic: 164.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.622348484503359 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0390 -0.7300  0.0346  0.9118  3.7101 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01146    0.08693 115.164  < 2e-16 ***
## category_code_LT01_4_count   0.84273    0.08740   9.642  < 2e-16 ***
## category_code_LT01_5_count   0.92709    0.06175  15.014  < 2e-16 ***
## category_code_LT01_11_count  0.46209    0.10984   4.207 3.07e-05 ***
## category_code_LT01_13_count  0.08816    0.24361   0.362    0.718    
## category_code_LT01_16_count  1.08053    1.16341   0.929    0.353    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 492 degrees of freedom
## Multiple R-squared:  0.6261, Adjusted R-squared:  0.6223 
## F-statistic: 164.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.621705514902868 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0405 -0.7315  0.0329  0.9195  3.7056 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01288    0.08708 114.986  < 2e-16 ***
## category_code_LT01_4_count   0.84195    0.08866   9.497  < 2e-16 ***
## category_code_LT01_5_count   0.92734    0.06209  14.936  < 2e-16 ***
## category_code_LT01_11_count  0.46654    0.10991   4.245 2.62e-05 ***
## category_code_LT01_14_count  0.10739    0.32755   0.328    0.743    
## category_code_LT01_15_count  0.11728    0.75034   0.156    0.876    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 492 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.6217 
## F-statistic: 164.4 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.622356006890751 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0392 -0.7306  0.0388  0.9210  3.7077 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01301    0.08700 115.086  < 2e-16 ***
## category_code_LT01_4_count   0.84036    0.08823   9.525  < 2e-16 ***
## category_code_LT01_5_count   0.92524    0.06206  14.909  < 2e-16 ***
## category_code_LT01_11_count  0.46332    0.10968   4.224 2.86e-05 ***
## category_code_LT01_14_count  0.12293    0.32765   0.375    0.708    
## category_code_LT01_16_count  1.08698    1.16406   0.934    0.351    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 492 degrees of freedom
## Multiple R-squared:  0.6262, Adjusted R-squared:  0.6224 
## F-statistic: 164.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.622274783734297 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0396 -0.7306  0.0336  0.9191  3.7092 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01164    0.08694 115.157  < 2e-16 ***
## category_code_LT01_4_count   0.84441    0.08736   9.665  < 2e-16 ***
## category_code_LT01_5_count   0.92783    0.06174  15.027  < 2e-16 ***
## category_code_LT01_11_count  0.46313    0.10989   4.214 2.98e-05 ***
## category_code_LT01_15_count  0.14022    0.75007   0.187    0.852    
## category_code_LT01_16_count  1.07196    1.16329   0.921    0.357    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 492 degrees of freedom
## Multiple R-squared:  0.6261, Adjusted R-squared:  0.6223 
## F-statistic: 164.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.608677454564014 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0446 -0.7902 -0.0093  0.9252  4.0302 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01163    0.08859 113.008   <2e-16 ***
## category_code_LT01_4_count   1.06989    0.07037  15.205   <2e-16 ***
## category_code_LT01_5_count   0.93506    0.06334  14.763   <2e-16 ***
## category_code_LT01_12_count  0.19706    0.20852   0.945    0.345    
## category_code_LT01_13_count  0.13505    0.24749   0.546    0.586    
## category_code_LT01_14_count  0.12215    0.33397   0.366    0.715    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 492 degrees of freedom
## Multiple R-squared:  0.6126, Adjusted R-squared:  0.6087 
## F-statistic: 155.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.608756424004072 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0449 -0.7892  0.0145  0.9317  4.0317 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01014    0.08850 113.107   <2e-16 ***
## category_code_LT01_4_count   1.06894    0.06998  15.275   <2e-16 ***
## category_code_LT01_5_count   0.93758    0.06304  14.872   <2e-16 ***
## category_code_LT01_12_count  0.20395    0.20791   0.981    0.327    
## category_code_LT01_13_count  0.14211    0.24793   0.573    0.567    
## category_code_LT01_15_count  0.36831    0.76285   0.483    0.629    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 492 degrees of freedom
## Multiple R-squared:  0.6127, Adjusted R-squared:  0.6088 
## F-statistic: 155.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.609515308699081 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0432 -0.7997  0.0115  0.9337  4.0317 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01015    0.08842 113.217   <2e-16 ***
## category_code_LT01_4_count   1.06985    0.06875  15.562   <2e-16 ***
## category_code_LT01_5_count   0.93514    0.06301  14.841   <2e-16 ***
## category_code_LT01_12_count  0.20227    0.20770   0.974    0.331    
## category_code_LT01_13_count  0.14370    0.24736   0.581    0.562    
## category_code_LT01_16_count  1.28916    1.18191   1.091    0.276    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 492 degrees of freedom
## Multiple R-squared:  0.6134, Adjusted R-squared:  0.6095 
## F-statistic: 156.2 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.608597273204575 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0457 -0.7916 -0.0140  0.9245  4.0301 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01181    0.08860 113.000   <2e-16 ***
## category_code_LT01_4_count   1.07092    0.07046  15.198   <2e-16 ***
## category_code_LT01_5_count   0.93626    0.06333  14.784   <2e-16 ***
## category_code_LT01_12_count  0.20171    0.20847   0.968    0.334    
## category_code_LT01_14_count  0.11966    0.33403   0.358    0.720    
## category_code_LT01_15_count  0.33799    0.76163   0.444    0.657    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 492 degrees of freedom
## Multiple R-squared:  0.6125, Adjusted R-squared:  0.6086 
## F-statistic: 155.6 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.609385111603992 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0440 -0.8016 -0.0219  0.9285  4.0298 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01204    0.08851 113.117   <2e-16 ***
## category_code_LT01_4_count   1.07048    0.06945  15.414   <2e-16 ***
## category_code_LT01_5_count   0.93350    0.06330  14.747   <2e-16 ***
## category_code_LT01_12_count  0.19925    0.20824   0.957    0.339    
## category_code_LT01_14_count  0.13910    0.33406   0.416    0.677    
## category_code_LT01_16_count  1.29013    1.18283   1.091    0.276    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 492 degrees of freedom
## Multiple R-squared:  0.6133, Adjusted R-squared:  0.6094 
## F-statistic: 156.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609428642453154 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0443 -0.7952  0.0090  0.9416  4.0315 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01037    0.08842 113.209   <2e-16 ***
## category_code_LT01_4_count   1.07078    0.06889  15.544   <2e-16 ***
## category_code_LT01_5_count   0.93638    0.06300  14.863   <2e-16 ***
## category_code_LT01_12_count  0.20711    0.20764   0.997    0.319    
## category_code_LT01_15_count  0.36358    0.76103   0.478    0.633    
## category_code_LT01_16_count  1.28153    1.18181   1.084    0.279    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 492 degrees of freedom
## Multiple R-squared:  0.6134, Adjusted R-squared:  0.6094 
## F-statistic: 156.1 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.608140620799419 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0506 -0.7945  0.0020  0.9255  4.0284 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01351    0.08863 112.983   <2e-16 ***
## category_code_LT01_4_count   1.07956    0.06967  15.496   <2e-16 ***
## category_code_LT01_5_count   0.94093    0.06312  14.908   <2e-16 ***
## category_code_LT01_13_count  0.14918    0.24803   0.601    0.548    
## category_code_LT01_14_count  0.14434    0.33326   0.433    0.665    
## category_code_LT01_15_count  0.35632    0.76346   0.467    0.641    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.41 on 492 degrees of freedom
## Multiple R-squared:  0.6121, Adjusted R-squared:  0.6081 
## F-statistic: 155.3 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.608955033817944 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0488 -0.7929  0.0028  0.9278  4.0282 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01372    0.08854 113.103   <2e-16 ***
## category_code_LT01_4_count   1.07897    0.06857  15.735   <2e-16 ***
## category_code_LT01_5_count   0.93800    0.06309  14.868   <2e-16 ***
## category_code_LT01_13_count  0.15119    0.24743   0.611    0.541    
## category_code_LT01_14_count  0.16399    0.33327   0.492    0.623    
## category_code_LT01_16_count  1.32014    1.18412   1.115    0.265    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 492 degrees of freedom
## Multiple R-squared:  0.6129, Adjusted R-squared:  0.609 
## F-statistic: 155.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.608964581855565 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0494 -0.7867  0.0035  0.9288  4.0301 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01182    0.08846 113.180   <2e-16 ***
## category_code_LT01_4_count   1.08050    0.06779  15.940   <2e-16 ***
## category_code_LT01_5_count   0.94159    0.06274  15.007   <2e-16 ***
## category_code_LT01_13_count  0.15870    0.24792   0.640    0.522    
## category_code_LT01_15_count  0.38461    0.76293   0.504    0.614    
## category_code_LT01_16_count  1.30944    1.18323   1.107    0.269    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 492 degrees of freedom
## Multiple R-squared:  0.6129, Adjusted R-squared:  0.609 
## F-statistic: 155.8 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.608826326232421 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0501 -0.8006  0.0041  0.9278  4.0279 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01398    0.08855 113.090   <2e-16 ***
## category_code_LT01_4_count   1.08106    0.06853  15.775   <2e-16 ***
## category_code_LT01_5_count   0.93948    0.06308  14.894   <2e-16 ***
## category_code_LT01_14_count  0.16184    0.33334   0.486    0.628    
## category_code_LT01_15_count  0.35013    0.76160   0.460    0.646    
## category_code_LT01_16_count  1.31044    1.18407   1.107    0.269    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 492 degrees of freedom
## Multiple R-squared:  0.6128, Adjusted R-squared:  0.6088 
## F-statistic: 155.7 on 5 and 492 DF,  p-value: < 2.2e-16
## 
## ########################################
## i:  6 
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count 0.646829461246844 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9396 -0.7271  0.0331  0.8528  3.5098 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.92222    0.08503 116.686  < 2e-16 ***
## category_code_LT01_1_count  0.22549    0.08665   2.602  0.00954 ** 
## category_code_LT01_2_count  0.45094    0.09092   4.959 9.76e-07 ***
## category_code_LT01_3_count  0.19254    0.11246   1.712  0.08752 .  
## category_code_LT01_4_count  0.50011    0.10215   4.896 1.33e-06 ***
## category_code_LT01_5_count  0.91254    0.06038  15.114  < 2e-16 ***
## category_code_LT01_6_count  0.26449    0.14952   1.769  0.07753 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.338 on 491 degrees of freedom
## Multiple R-squared:  0.6511, Adjusted R-squared:  0.6468 
## F-statistic: 152.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count 0.648760100682066 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9517 -0.7219  0.0118  0.8344  3.4965 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93233    0.08473 117.220  < 2e-16 ***
## category_code_LT01_1_count  0.21781    0.08653   2.517   0.0122 *  
## category_code_LT01_2_count  0.45763    0.08933   5.123 4.33e-07 ***
## category_code_LT01_3_count  0.20069    0.11196   1.792   0.0737 .  
## category_code_LT01_4_count  0.47781    0.10277   4.649 4.28e-06 ***
## category_code_LT01_5_count  0.91543    0.05998  15.263  < 2e-16 ***
## category_code_LT01_7_count  0.36245    0.14992   2.418   0.0160 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.335 on 491 degrees of freedom
## Multiple R-squared:  0.653,  Adjusted R-squared:  0.6488 
## F-statistic:   154 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count 0.644827490525434 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9591 -0.7259  0.0495  0.8624  3.4836 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93019    0.08523 116.516  < 2e-16 ***
## category_code_LT01_1_count  0.23617    0.08678   2.722  0.00673 ** 
## category_code_LT01_2_count  0.48445    0.08911   5.437 8.57e-08 ***
## category_code_LT01_3_count  0.20573    0.11260   1.827  0.06829 .  
## category_code_LT01_4_count  0.52660    0.10135   5.196 2.99e-07 ***
## category_code_LT01_5_count  0.92914    0.06091  15.254  < 2e-16 ***
## category_code_LT01_8_count -0.15588    0.26584  -0.586  0.55789    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.6491, Adjusted R-squared:  0.6448 
## F-statistic: 151.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count 0.645764490043902 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9484 -0.7164  0.0956  0.8681  3.4987 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.92686    0.08509 116.658  < 2e-16 ***
## category_code_LT01_1_count  0.23134    0.08666   2.670  0.00785 ** 
## category_code_LT01_2_count  0.47301    0.08948   5.286 1.88e-07 ***
## category_code_LT01_3_count  0.18593    0.11335   1.640  0.10158    
## category_code_LT01_4_count  0.52317    0.10125   5.167 3.46e-07 ***
## category_code_LT01_5_count  0.91844    0.06027  15.238  < 2e-16 ***
## category_code_LT01_9_count  0.28279    0.22059   1.282  0.20045    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.34 on 491 degrees of freedom
## Multiple R-squared:   0.65,  Adjusted R-squared:  0.6458 
## F-statistic:   152 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count 0.644962118926615 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9370 -0.7261  0.0549  0.8712  3.4194 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91181    0.08831 112.235  < 2e-16 ***
## category_code_LT01_1_count   0.23722    0.08679   2.733   0.0065 ** 
## category_code_LT01_2_count   0.48057    0.08930   5.381 1.15e-07 ***
## category_code_LT01_3_count   0.19026    0.11423   1.666   0.0964 .  
## category_code_LT01_4_count   0.52464    0.10136   5.176 3.31e-07 ***
## category_code_LT01_5_count   0.92383    0.06020  15.346  < 2e-16 ***
## category_code_LT01_10_count  0.08047    0.11052   0.728   0.4669    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.6492, Adjusted R-squared:  0.645 
## F-statistic: 151.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count 0.645846607718405 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9594 -0.7248  0.0300  0.8593  3.4866 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93604    0.08525 116.558  < 2e-16 ***
## category_code_LT01_1_count   0.21807    0.08751   2.492    0.013 *  
## category_code_LT01_2_count   0.44142    0.09488   4.653 4.22e-06 ***
## category_code_LT01_3_count   0.17770    0.11421   1.556    0.120    
## category_code_LT01_4_count   0.49460    0.10400   4.756 2.60e-06 ***
## category_code_LT01_5_count   0.92111    0.06016  15.311  < 2e-16 ***
## category_code_LT01_11_count  0.15752    0.11881   1.326    0.186    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.34 on 491 degrees of freedom
## Multiple R-squared:  0.6501, Adjusted R-squared:  0.6458 
## F-statistic: 152.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count 0.64465102316476 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9551 -0.7261  0.0550  0.8652  3.4891 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92861    0.08522 116.511  < 2e-16 ***
## category_code_LT01_1_count   0.23769    0.08729   2.723   0.0067 ** 
## category_code_LT01_2_count   0.48863    0.08982   5.440 8.43e-08 ***
## category_code_LT01_3_count   0.20583    0.11269   1.826   0.0684 .  
## category_code_LT01_4_count   0.52719    0.10141   5.199 2.95e-07 ***
## category_code_LT01_5_count   0.92560    0.06051  15.296  < 2e-16 ***
## category_code_LT01_12_count -0.06376    0.20179  -0.316   0.7522    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6489, Adjusted R-squared:  0.6447 
## F-statistic: 151.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count 0.644585289579423 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9540 -0.7189  0.0617  0.8657  3.4908 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92870    0.08523 116.496  < 2e-16 ***
## category_code_LT01_1_count   0.23576    0.08757   2.692  0.00734 ** 
## category_code_LT01_2_count   0.48539    0.08919   5.442 8.31e-08 ***
## category_code_LT01_3_count   0.20435    0.11262   1.815  0.07020 .  
## category_code_LT01_4_count   0.52676    0.10147   5.191 3.07e-07 ***
## category_code_LT01_5_count   0.92394    0.06027  15.330  < 2e-16 ***
## category_code_LT01_13_count -0.02262    0.23825  -0.095  0.92441    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6489, Adjusted R-squared:  0.6446 
## F-statistic: 151.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count 0.644580066927905 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9540 -0.7182  0.0532  0.8657  3.4908 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92860    0.08535 116.332  < 2e-16 ***
## category_code_LT01_1_count   0.23501    0.08723   2.694   0.0073 ** 
## category_code_LT01_2_count   0.48531    0.08927   5.436 8.59e-08 ***
## category_code_LT01_3_count   0.20411    0.11286   1.809   0.0711 .  
## category_code_LT01_4_count   0.52683    0.10200   5.165 3.50e-07 ***
## category_code_LT01_5_count   0.92403    0.06062  15.244  < 2e-16 ***
## category_code_LT01_14_count -0.01356    0.31999  -0.042   0.9662    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6489, Adjusted R-squared:  0.6446 
## F-statistic: 151.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count 0.6448986429675 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9521 -0.7169  0.0613  0.8673  3.4930 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92733    0.08521 116.501  < 2e-16 ***
## category_code_LT01_1_count   0.24397    0.08786   2.777   0.0057 ** 
## category_code_LT01_2_count   0.48656    0.08912   5.460 7.59e-08 ***
## category_code_LT01_3_count   0.21208    0.11315   1.874   0.0615 .  
## category_code_LT01_4_count   0.52540    0.10135   5.184 3.18e-07 ***
## category_code_LT01_5_count   0.92318    0.06021  15.332  < 2e-16 ***
## category_code_LT01_15_count -0.49329    0.74174  -0.665   0.5063    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.6492, Adjusted R-squared:  0.6449 
## F-statistic: 151.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_16_count 0.644627458196133 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9541 -0.7186  0.0589  0.8654  3.4909 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92906    0.08522 116.507  < 2e-16 ***
## category_code_LT01_1_count   0.23551    0.08683   2.712  0.00691 ** 
## category_code_LT01_2_count   0.48286    0.08954   5.393 1.08e-07 ***
## category_code_LT01_3_count   0.20134    0.11324   1.778  0.07601 .  
## category_code_LT01_4_count   0.52773    0.10152   5.198 2.95e-07 ***
## category_code_LT01_5_count   0.92354    0.06023  15.333  < 2e-16 ***
## category_code_LT01_16_count  0.29613    1.14172   0.259  0.79546    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6489, Adjusted R-squared:  0.6446 
## F-statistic: 151.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 0.637719986279373 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9636 -0.7468  0.0516  0.8345  3.4752 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.92817    0.08613 115.266  < 2e-16 ***
## category_code_LT01_1_count  0.31666    0.08429   3.757 0.000193 ***
## category_code_LT01_2_count  0.59295    0.08377   7.078 5.08e-12 ***
## category_code_LT01_3_count  0.32076    0.10961   2.926 0.003587 ** 
## category_code_LT01_5_count  0.93858    0.06071  15.460  < 2e-16 ***
## category_code_LT01_6_count  0.36688    0.14983   2.449 0.014690 *  
## category_code_LT01_7_count  0.49576    0.14933   3.320 0.000967 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.356 on 491 degrees of freedom
## Multiple R-squared:  0.6421, Adjusted R-squared:  0.6377 
## F-statistic: 146.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 0.629903900635273 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9771 -0.7923  0.0272  0.8432  3.4679 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.92529    0.08708 113.984  < 2e-16 ***
## category_code_LT01_1_count  0.35946    0.08430   4.264 2.41e-05 ***
## category_code_LT01_2_count  0.65880    0.08219   8.015 8.08e-15 ***
## category_code_LT01_3_count  0.34846    0.11051   3.153  0.00171 ** 
## category_code_LT01_5_count  0.96221    0.06180  15.569  < 2e-16 ***
## category_code_LT01_6_count  0.37459    0.15155   2.472  0.01378 *  
## category_code_LT01_8_count -0.17603    0.27157  -0.648  0.51716    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6344, Adjusted R-squared:  0.6299 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 0.630851398956744 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9659 -0.7717  0.0705  0.8568  3.4712 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.92196    0.08695 114.115  < 2e-16 ***
## category_code_LT01_1_count  0.35399    0.08421   4.204 3.12e-05 ***
## category_code_LT01_2_count  0.64726    0.08266   7.831 3.01e-14 ***
## category_code_LT01_3_count  0.32754    0.11138   2.941  0.00343 ** 
## category_code_LT01_5_count  0.95085    0.06119  15.539  < 2e-16 ***
## category_code_LT01_6_count  0.36405    0.15133   2.406  0.01651 *  
## category_code_LT01_9_count  0.29209    0.22525   1.297  0.19534    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6353, Adjusted R-squared:  0.6309 
## F-statistic: 142.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 0.629761582154813 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9606 -0.8060  0.0523  0.8552  3.4807 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91250    0.09018 109.914  < 2e-16 ***
## category_code_LT01_1_count   0.35998    0.08440   4.265 2.39e-05 ***
## category_code_LT01_2_count   0.65830    0.08227   8.002 8.88e-15 ***
## category_code_LT01_3_count   0.33798    0.11216   3.013  0.00272 ** 
## category_code_LT01_5_count   0.95679    0.06115  15.648  < 2e-16 ***
## category_code_LT01_6_count   0.36013    0.15308   2.352  0.01904 *  
## category_code_LT01_10_count  0.05484    0.11403   0.481  0.63081    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6342, Adjusted R-squared:  0.6298 
## F-statistic: 141.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 0.633082608567077 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9788 -0.7761  0.0903  0.8295  3.4570 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93618    0.08686 114.393  < 2e-16 ***
## category_code_LT01_1_count   0.31903    0.08581   3.718 0.000224 ***
## category_code_LT01_2_count   0.57236    0.09131   6.268 8.01e-10 ***
## category_code_LT01_3_count   0.28992    0.11316   2.562 0.010700 *  
## category_code_LT01_5_count   0.94899    0.06096  15.569  < 2e-16 ***
## category_code_LT01_6_count   0.33108    0.15190   2.180 0.029765 *  
## category_code_LT01_11_count  0.25640    0.11855   2.163 0.031043 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.364 on 491 degrees of freedom
## Multiple R-squared:  0.6375, Adjusted R-squared:  0.6331 
## F-statistic: 143.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 0.629711036147685 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9727 -0.7968  0.0355  0.8396  3.4697 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92343    0.08707 113.965  < 2e-16 ***
## category_code_LT01_1_count   0.36185    0.08485   4.264 2.41e-05 ***
## category_code_LT01_2_count   0.66422    0.08283   8.019 7.85e-15 ***
## category_code_LT01_3_count   0.34896    0.11060   3.155   0.0017 ** 
## category_code_LT01_5_count   0.95855    0.06139  15.613  < 2e-16 ***
## category_code_LT01_6_count   0.37649    0.15212   2.475   0.0137 *  
## category_code_LT01_12_count -0.08380    0.20680  -0.405   0.6855    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6342, Adjusted R-squared:  0.6297 
## F-statistic: 141.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 0.629611739113646 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9714 -0.7910  0.0474  0.8425  3.4692 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92398    0.08709 113.957  < 2e-16 ***
## category_code_LT01_1_count   0.35544    0.08538   4.163 3.71e-05 ***
## category_code_LT01_2_count   0.65902    0.08240   7.997 9.20e-15 ***
## category_code_LT01_3_count   0.34703    0.11054   3.139  0.00179 ** 
## category_code_LT01_5_count   0.95580    0.06121  15.615  < 2e-16 ***
## category_code_LT01_6_count   0.37146    0.15154   2.451  0.01458 *  
## category_code_LT01_13_count  0.04384    0.24307   0.180  0.85695    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6341, Adjusted R-squared:  0.6296 
## F-statistic: 141.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 0.629994603219543 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9702 -0.7941  0.0541  0.8488  3.4662 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92694    0.08714 113.920  < 2e-16 ***
## category_code_LT01_1_count   0.34819    0.08528   4.083 5.20e-05 ***
## category_code_LT01_2_count   0.65078    0.08312   7.829 3.05e-14 ***
## category_code_LT01_3_count   0.34925    0.11051   3.160  0.00167 ** 
## category_code_LT01_5_count   0.94985    0.06174  15.385  < 2e-16 ***
## category_code_LT01_6_count   0.38071    0.15202   2.504  0.01259 *  
## category_code_LT01_14_count  0.23956    0.32581   0.735  0.46253    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:   0.63 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 0.630040121915482 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9691 -0.7887  0.0522  0.8448  3.4712 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92200    0.08706 113.965  < 2e-16 ***
## category_code_LT01_1_count   0.36853    0.08536   4.317 1.91e-05 ***
## category_code_LT01_2_count   0.66086    0.08216   8.044 6.59e-15 ***
## category_code_LT01_3_count   0.35574    0.11102   3.204  0.00144 ** 
## category_code_LT01_5_count   0.95538    0.06112  15.630  < 2e-16 ***
## category_code_LT01_6_count   0.37328    0.15144   2.465  0.01405 *  
## category_code_LT01_15_count -0.58705    0.75719  -0.775  0.43853    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:   0.63 
## F-statistic: 142.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 0.629632695561587 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9715 -0.7911  0.0465  0.8454  3.4692 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92398    0.08708 113.963  < 2e-16 ***
## category_code_LT01_1_count   0.35886    0.08439   4.252 2.53e-05 ***
## category_code_LT01_2_count   0.65782    0.08270   7.954 1.25e-14 ***
## category_code_LT01_3_count   0.34433    0.11114   3.098  0.00206 ** 
## category_code_LT01_5_count   0.95603    0.06116  15.632  < 2e-16 ***
## category_code_LT01_6_count   0.37471    0.15232   2.460  0.01424 *  
## category_code_LT01_16_count  0.28742    1.17036   0.246  0.80611    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6341, Adjusted R-squared:  0.6296 
## F-statistic: 141.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 0.633619154420195 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9921 -0.7439  0.0316  0.7972  3.4539 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93924    0.08657 114.817  < 2e-16 ***
## category_code_LT01_1_count  0.34080    0.08429   4.043 6.12e-05 ***
## category_code_LT01_2_count  0.65549    0.08011   8.182 2.41e-15 ***
## category_code_LT01_3_count  0.35036    0.10964   3.196 0.001485 ** 
## category_code_LT01_5_count  0.96367    0.06125  15.733  < 2e-16 ***
## category_code_LT01_7_count  0.50166    0.15023   3.339 0.000904 ***
## category_code_LT01_8_count -0.17772    0.27013  -0.658 0.510905    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.363 on 491 degrees of freedom
## Multiple R-squared:  0.638,  Adjusted R-squared:  0.6336 
## F-statistic: 144.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 0.634180928049549 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9814 -0.7356  0.0471  0.7561  3.4574 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93580    0.08648 114.890  < 2e-16 ***
## category_code_LT01_1_count  0.33685    0.08422   3.999 7.33e-05 ***
## category_code_LT01_2_count  0.64681    0.08053   8.032 7.18e-15 ***
## category_code_LT01_3_count  0.33281    0.11053   3.011  0.00274 ** 
## category_code_LT01_5_count  0.95327    0.06064  15.721  < 2e-16 ***
## category_code_LT01_7_count  0.48375    0.15067   3.211  0.00141 ** 
## category_code_LT01_9_count  0.24522    0.22503   1.090  0.27637    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.362 on 491 degrees of freedom
## Multiple R-squared:  0.6386, Adjusted R-squared:  0.6342 
## F-statistic: 144.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 0.633547699039975 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9725 -0.7724  0.0453  0.8210  3.4694 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92376    0.08978 110.540  < 2e-16 ***
## category_code_LT01_1_count   0.34150    0.08436   4.048 6.00e-05 ***
## category_code_LT01_2_count   0.65312    0.08032   8.132 3.48e-15 ***
## category_code_LT01_3_count   0.33735    0.11143   3.027  0.00260 ** 
## category_code_LT01_5_count   0.95777    0.06056  15.816  < 2e-16 ***
## category_code_LT01_7_count   0.49189    0.15063   3.266  0.00117 ** 
## category_code_LT01_10_count  0.06536    0.11258   0.581  0.56182    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.363 on 491 degrees of freedom
## Multiple R-squared:  0.638,  Adjusted R-squared:  0.6335 
## F-statistic: 144.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 0.635383725912097 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9912 -0.7672  0.0435  0.8205  3.4471 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94605    0.08647 115.024  < 2e-16 ***
## category_code_LT01_1_count   0.31189    0.08562   3.643 0.000299 ***
## category_code_LT01_2_count   0.59038    0.08911   6.625 9.12e-11 ***
## category_code_LT01_3_count   0.30463    0.11250   2.708 0.007007 ** 
## category_code_LT01_5_count   0.95251    0.06048  15.749  < 2e-16 ***
## category_code_LT01_7_count   0.43414    0.15466   2.807 0.005200 ** 
## category_code_LT01_11_count  0.20307    0.12112   1.677 0.094248 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.36 on 491 degrees of freedom
## Multiple R-squared:  0.6398, Adjusted R-squared:  0.6354 
## F-statistic: 145.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 0.633313414426661 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9868 -0.7330  0.0274  0.8053  3.4556 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93753    0.08657 114.792  < 2e-16 ***
## category_code_LT01_1_count   0.34084    0.08497   4.012 6.97e-05 ***
## category_code_LT01_2_count   0.65845    0.08114   8.115 3.93e-15 ***
## category_code_LT01_3_count   0.34977    0.10980   3.186 0.001536 ** 
## category_code_LT01_5_count   0.95855    0.06090  15.739  < 2e-16 ***
## category_code_LT01_7_count   0.49846    0.15023   3.318 0.000974 ***
## category_code_LT01_12_count -0.03114    0.20492  -0.152 0.879281    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.364 on 491 degrees of freedom
## Multiple R-squared:  0.6377, Adjusted R-squared:  0.6333 
## F-statistic: 144.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 0.633340868293599 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9864 -0.7352  0.0333  0.8066  3.4557 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93742    0.08657 114.792  < 2e-16 ***
## category_code_LT01_1_count   0.34215    0.08513   4.019 6.76e-05 ***
## category_code_LT01_2_count   0.65721    0.08018   8.197 2.17e-15 ***
## category_code_LT01_3_count   0.34888    0.10966   3.182 0.001557 ** 
## category_code_LT01_5_count   0.95807    0.06061  15.808  < 2e-16 ***
## category_code_LT01_7_count   0.50272    0.15114   3.326 0.000946 ***
## category_code_LT01_13_count -0.05951    0.24325  -0.245 0.806823    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.364 on 491 degrees of freedom
## Multiple R-squared:  0.6378, Adjusted R-squared:  0.6333 
## F-statistic: 144.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 0.633347773728052 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9861 -0.7576  0.0356  0.8083  3.4544 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93880    0.08668 114.662  < 2e-16 ***
## category_code_LT01_1_count   0.33625    0.08505   3.954 8.83e-05 ***
## category_code_LT01_2_count   0.65424    0.08059   8.118 3.85e-15 ***
## category_code_LT01_3_count   0.35011    0.10974   3.190  0.00151 ** 
## category_code_LT01_5_count   0.95560    0.06105  15.654  < 2e-16 ***
## category_code_LT01_7_count   0.49559    0.15067   3.289  0.00108 ** 
## category_code_LT01_14_count  0.08518    0.32402   0.263  0.79275    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.364 on 491 degrees of freedom
## Multiple R-squared:  0.6378, Adjusted R-squared:  0.6333 
## F-statistic: 144.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 0.633522536054975 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9847 -0.7419  0.0371  0.8013  3.4568 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93635    0.08657 114.773  < 2e-16 ***
## category_code_LT01_1_count   0.34724    0.08552   4.060 5.70e-05 ***
## category_code_LT01_2_count   0.65798    0.08015   8.209 1.98e-15 ***
## category_code_LT01_3_count   0.35537    0.11025   3.223  0.00135 ** 
## category_code_LT01_5_count   0.95720    0.06056  15.805  < 2e-16 ***
## category_code_LT01_7_count   0.49423    0.15040   3.286  0.00109 ** 
## category_code_LT01_15_count -0.41552    0.75452  -0.551  0.58208    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.363 on 491 degrees of freedom
## Multiple R-squared:  0.6379, Adjusted R-squared:  0.6335 
## F-statistic: 144.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 0.633299313054336 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9863 -0.7398  0.0364  0.8075  3.4555 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93770    0.08658 114.785  < 2e-16 ***
## category_code_LT01_1_count   0.33952    0.08442   4.022 6.69e-05 ***
## category_code_LT01_2_count   0.65607    0.08042   8.158 2.87e-15 ***
## category_code_LT01_3_count   0.34826    0.11016   3.161 0.001668 ** 
## category_code_LT01_5_count   0.95758    0.06058  15.807  < 2e-16 ***
## category_code_LT01_7_count   0.49887    0.15027   3.320 0.000968 ***
## category_code_LT01_16_count  0.07517    1.15850   0.065 0.948294    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.364 on 491 degrees of freedom
## Multiple R-squared:  0.6377, Adjusted R-squared:  0.6333 
## F-statistic: 144.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 0.626769074424441 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9933 -0.7764  0.0531  0.8062  3.4605 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93261    0.08737 113.680  < 2e-16 ***
## category_code_LT01_1_count  0.37795    0.08420   4.489 8.94e-06 ***
## category_code_LT01_2_count  0.70907    0.07890   8.987  < 2e-16 ***
## category_code_LT01_3_count  0.35552    0.11145   3.190  0.00151 ** 
## category_code_LT01_5_count  0.97501    0.06174  15.791  < 2e-16 ***
## category_code_LT01_8_count -0.16206    0.27265  -0.594  0.55251    
## category_code_LT01_9_count  0.31496    0.22647   1.391  0.16493    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 0.625834650275205 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9794 -0.7527  0.0200  0.8177  3.4785 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91463    0.09068 109.336  < 2e-16 ***
## category_code_LT01_1_count   0.38502    0.08430   4.567 6.26e-06 ***
## category_code_LT01_2_count   0.71789    0.07860   9.133  < 2e-16 ***
## category_code_LT01_3_count   0.35981    0.11242   3.201  0.00146 ** 
## category_code_LT01_5_count   0.98092    0.06168  15.904  < 2e-16 ***
## category_code_LT01_8_count  -0.15511    0.27292  -0.568  0.57006    
## category_code_LT01_10_count  0.09513    0.11345   0.839  0.40213    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6304, Adjusted R-squared:  0.6258 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 0.629711379784417 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0042 -0.7668  0.0631  0.8315  3.4460 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94718    0.08717 114.114  < 2e-16 ***
## category_code_LT01_1_count   0.33619    0.08597   3.911 0.000105 ***
## category_code_LT01_2_count   0.61867    0.08923   6.934  1.3e-11 ***
## category_code_LT01_3_count   0.30969    0.11341   2.731 0.006546 ** 
## category_code_LT01_5_count   0.96976    0.06153  15.761  < 2e-16 ***
## category_code_LT01_8_count  -0.13219    0.27154  -0.487 0.626595    
## category_code_LT01_11_count  0.28607    0.11826   2.419 0.015930 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6342, Adjusted R-squared:  0.6297 
## F-statistic: 141.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 0.625317912691046 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0000 -0.7524  0.0468  0.8288  3.4586 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93458    0.08753 113.495  < 2e-16 ***
## category_code_LT01_1_count   0.38415    0.08497   4.521 7.71e-06 ***
## category_code_LT01_2_count   0.72620    0.07933   9.154  < 2e-16 ***
## category_code_LT01_3_count   0.37802    0.11070   3.415 0.000691 ***
## category_code_LT01_5_count   0.98179    0.06201  15.832  < 2e-16 ***
## category_code_LT01_8_count  -0.14872    0.27320  -0.544 0.586439    
## category_code_LT01_12_count -0.03279    0.20725  -0.158 0.874343    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6253 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 0.625304625257297 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9993 -0.7546  0.0484  0.8296  3.4584 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93476    0.08754 113.493  < 2e-16 ***
## category_code_LT01_1_count   0.38129    0.08540   4.465 9.95e-06 ***
## category_code_LT01_2_count   0.72374    0.07847   9.223  < 2e-16 ***
## category_code_LT01_3_count   0.37710    0.11058   3.410 0.000702 ***
## category_code_LT01_5_count   0.98057    0.06180  15.866  < 2e-16 ***
## category_code_LT01_8_count  -0.14870    0.27358  -0.544 0.587012    
## category_code_LT01_13_count  0.02138    0.24488   0.087 0.930460    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6253 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 0.62550487780541 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9990 -0.7523  0.0443  0.8217  3.4561 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93710    0.08763 113.396  < 2e-16 ***
## category_code_LT01_1_count   0.37606    0.08518   4.415 1.24e-05 ***
## category_code_LT01_2_count   0.71882    0.07896   9.104  < 2e-16 ***
## category_code_LT01_3_count   0.37919    0.11061   3.428 0.000659 ***
## category_code_LT01_5_count   0.97672    0.06221  15.699  < 2e-16 ***
## category_code_LT01_8_count  -0.15211    0.27300  -0.557 0.577667    
## category_code_LT01_14_count  0.16972    0.32652   0.520 0.603447    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6255 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 0.62569084222635 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9973 -0.7606  0.0547  0.8291  3.4601 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93305    0.08752 113.499  < 2e-16 ***
## category_code_LT01_1_count   0.39251    0.08542   4.595  5.5e-06 ***
## category_code_LT01_2_count   0.72533    0.07828   9.266  < 2e-16 ***
## category_code_LT01_3_count   0.38529    0.11110   3.468  0.00057 ***
## category_code_LT01_5_count   0.98009    0.06170  15.885  < 2e-16 ***
## category_code_LT01_8_count  -0.14936    0.27291  -0.547  0.58442    
## category_code_LT01_15_count -0.54605    0.76146  -0.717  0.47365    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6257 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 0.625299012422337 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9995 -0.7550  0.0481  0.8294  3.4584 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93471    0.08754 113.486  < 2e-16 ***
## category_code_LT01_1_count   0.38256    0.08446   4.529 7.43e-06 ***
## category_code_LT01_2_count   0.72408    0.07856   9.217  < 2e-16 ***
## category_code_LT01_3_count   0.37700    0.11106   3.395 0.000743 ***
## category_code_LT01_5_count   0.98085    0.06172  15.891  < 2e-16 ***
## category_code_LT01_8_count  -0.15041    0.27339  -0.550 0.582466    
## category_code_LT01_16_count  0.01919    1.17223   0.016 0.986944    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6253 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 0.626867362174898 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9716 -0.7814  0.0658  0.8048  3.4786 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91459    0.09054 109.507  < 2e-16 ***
## category_code_LT01_1_count   0.37865    0.08421   4.496 8.64e-06 ***
## category_code_LT01_2_count   0.70536    0.07914   8.913  < 2e-16 ***
## category_code_LT01_3_count   0.34098    0.11307   3.016   0.0027 ** 
## category_code_LT01_5_count   0.96968    0.06103  15.889  < 2e-16 ***
## category_code_LT01_9_count   0.29506    0.22745   1.297   0.1952    
## category_code_LT01_10_count  0.07909    0.11383   0.695   0.4875    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6314, Adjusted R-squared:  0.6269 
## F-statistic: 140.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 0.630825900397986 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9937 -0.7334  0.0692  0.8479  3.4493 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94383    0.08702 114.265  < 2e-16 ***
## category_code_LT01_1_count   0.33092    0.08582   3.856 0.000131 ***
## category_code_LT01_2_count   0.60603    0.08960   6.764 3.84e-11 ***
## category_code_LT01_3_count   0.28878    0.11415   2.530 0.011724 *  
## category_code_LT01_5_count   0.95940    0.06085  15.768  < 2e-16 ***
## category_code_LT01_9_count   0.29537    0.22521   1.311 0.190302    
## category_code_LT01_11_count  0.28324    0.11809   2.398 0.016835 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6353, Adjusted R-squared:  0.6308 
## F-statistic: 142.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 0.626522106820004 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9887 -0.7782  0.0693  0.8078  3.4621 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93109    0.08737 113.665  < 2e-16 ***
## category_code_LT01_1_count   0.37814    0.08486   4.456 1.04e-05 ***
## category_code_LT01_2_count   0.71198    0.07994   8.906  < 2e-16 ***
## category_code_LT01_3_count   0.35531    0.11161   3.184  0.00155 ** 
## category_code_LT01_5_count   0.97052    0.06138  15.811  < 2e-16 ***
## category_code_LT01_9_count   0.31051    0.22644   1.371  0.17091    
## category_code_LT01_12_count -0.03486    0.20680  -0.169  0.86623    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.631,  Adjusted R-squared:  0.6265 
## F-statistic:   140 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 0.626536618505105 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9878 -0.7781  0.0640  0.8114  3.4618 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93139    0.08737 113.667  < 2e-16 ***
## category_code_LT01_1_count   0.37337    0.08529   4.378 1.47e-05 ***
## category_code_LT01_2_count   0.70853    0.07914   8.953  < 2e-16 ***
## category_code_LT01_3_count   0.35400    0.11148   3.175  0.00159 ** 
## category_code_LT01_5_count   0.96883    0.06112  15.851  < 2e-16 ***
## category_code_LT01_9_count   0.31420    0.22698   1.384  0.16691    
## category_code_LT01_13_count  0.05330    0.24460   0.218  0.82759    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.631,  Adjusted R-squared:  0.6265 
## F-statistic:   140 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 0.626633788052392 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9878 -0.7791  0.0649  0.8100  3.4600 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93317    0.08748 113.542  < 2e-16 ***
## category_code_LT01_1_count   0.37125    0.08505   4.365 1.55e-05 ***
## category_code_LT01_2_count   0.70582    0.07948   8.881  < 2e-16 ***
## category_code_LT01_3_count   0.35644    0.11156   3.195  0.00149 ** 
## category_code_LT01_5_count   0.96621    0.06154  15.701  < 2e-16 ***
## category_code_LT01_9_count   0.30414    0.22695   1.340  0.18082    
## category_code_LT01_14_count  0.13682    0.32679   0.419  0.67564    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6311, Adjusted R-squared:  0.6266 
## F-statistic:   140 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 0.626828562201142 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9862 -0.7764  0.0761  0.8095  3.4634 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92975    0.08736 113.662  < 2e-16 ***
## category_code_LT01_1_count   0.38564    0.08534   4.519 7.79e-06 ***
## category_code_LT01_2_count   0.71121    0.07891   9.013  < 2e-16 ***
## category_code_LT01_3_count   0.36230    0.11208   3.233  0.00131 ** 
## category_code_LT01_5_count   0.96892    0.06103  15.875  < 2e-16 ***
## category_code_LT01_9_count   0.30378    0.22659   1.341  0.18065    
## category_code_LT01_15_count -0.50006    0.76113  -0.657  0.51149    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 0.626501443025592 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9880 -0.7780  0.0642  0.8094  3.4620 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93115    0.08738 113.655  < 2e-16 ***
## category_code_LT01_1_count   0.37617    0.08434   4.460 1.02e-05 ***
## category_code_LT01_2_count   0.71004    0.07916   8.970  < 2e-16 ***
## category_code_LT01_3_count   0.35473    0.11194   3.169  0.00162 ** 
## category_code_LT01_5_count   0.96946    0.06106  15.878  < 2e-16 ***
## category_code_LT01_9_count   0.31088    0.22647   1.373  0.17047    
## category_code_LT01_16_count -0.04118    1.16906  -0.035  0.97192    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.631,  Adjusted R-squared:  0.6265 
## F-statistic: 139.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 0.630023249488358 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9806 -0.7724  0.0706  0.8270  3.4664 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92680    0.09032 109.911  < 2e-16 ***
## category_code_LT01_1_count   0.33711    0.08592   3.923 9.98e-05 ***
## category_code_LT01_2_count   0.61289    0.08946   6.851 2.21e-11 ***
## category_code_LT01_3_count   0.29171    0.11513   2.534   0.0116 *  
## category_code_LT01_5_count   0.96505    0.06076  15.884  < 2e-16 ***
## category_code_LT01_10_count  0.09101    0.11279   0.807   0.4201    
## category_code_LT01_11_count  0.28670    0.11818   2.426   0.0156 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:   0.63 
## F-statistic: 142.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 0.625620398701883 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9752 -0.7628  0.0241  0.8191  3.4799 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91326    0.09070 109.301  < 2e-16 ***
## category_code_LT01_1_count   0.38559    0.08496   4.538 7.14e-06 ***
## category_code_LT01_2_count   0.72107    0.07960   9.058  < 2e-16 ***
## category_code_LT01_3_count   0.35966    0.11254   3.196  0.00148 ** 
## category_code_LT01_5_count   0.97681    0.06129  15.938  < 2e-16 ***
## category_code_LT01_10_count  0.09452    0.11352   0.833  0.40546    
## category_code_LT01_12_count -0.04238    0.20717  -0.205  0.83800    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6256 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 0.625595351371455 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9746 -0.7630  0.0276  0.8234  3.4794 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91371    0.09071 109.294  < 2e-16 ***
## category_code_LT01_1_count   0.38211    0.08535   4.477 9.43e-06 ***
## category_code_LT01_2_count   0.71805    0.07878   9.115  < 2e-16 ***
## category_code_LT01_3_count   0.35869    0.11244   3.190  0.00151 ** 
## category_code_LT01_5_count   0.97528    0.06102  15.984  < 2e-16 ***
## category_code_LT01_10_count  0.09340    0.11352   0.823  0.41105    
## category_code_LT01_13_count  0.02318    0.24444   0.095  0.92447    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6256 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 0.625672295564193 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9762 -0.7604  0.0399  0.8340  3.4762 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91699    0.09127 108.651  < 2e-16 ***
## category_code_LT01_1_count   0.37894    0.08533   4.441 1.11e-05 ***
## category_code_LT01_2_count   0.71559    0.07911   9.046  < 2e-16 ***
## category_code_LT01_3_count   0.36162    0.11278   3.207  0.00143 ** 
## category_code_LT01_5_count   0.97279    0.06152  15.814  < 2e-16 ***
## category_code_LT01_10_count  0.08487    0.11656   0.728  0.46688    
## category_code_LT01_14_count  0.11119    0.33537   0.332  0.74037    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6257 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 0.626046836936742 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9711 -0.7598  0.0295  0.8130  3.4826 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91055    0.09072 109.248  < 2e-16 ***
## category_code_LT01_1_count   0.39442    0.08542   4.617 4.97e-06 ***
## category_code_LT01_2_count   0.71937    0.07858   9.154  < 2e-16 ***
## category_code_LT01_3_count   0.36643    0.11281   3.248  0.00124 ** 
## category_code_LT01_5_count   0.97473    0.06094  15.996  < 2e-16 ***
## category_code_LT01_10_count  0.09954    0.11364   0.876  0.38150    
## category_code_LT01_15_count -0.59171    0.76274  -0.776  0.43826    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6306, Adjusted R-squared:  0.626 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 0.625589042794292 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9746 -0.7636  0.0271  0.8223  3.4797 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91350    0.09070 109.296  < 2e-16 ***
## category_code_LT01_1_count   0.38325    0.08442   4.540 7.09e-06 ***
## category_code_LT01_2_count   0.71868    0.07887   9.113  < 2e-16 ***
## category_code_LT01_3_count   0.35895    0.11289   3.180  0.00157 ** 
## category_code_LT01_5_count   0.97553    0.06097  16.001  < 2e-16 ***
## category_code_LT01_10_count  0.09380    0.11348   0.827  0.40887    
## category_code_LT01_16_count -0.03148    1.17052  -0.027  0.97856    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6256 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 0.629931144665542 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0031 -0.7545  0.0544  0.8184  3.4467 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94648    0.08712 114.176  < 2e-16 ***
## category_code_LT01_1_count   0.33937    0.08613   3.940 9.32e-05 ***
## category_code_LT01_2_count   0.62086    0.08926   6.956 1.12e-11 ***
## category_code_LT01_3_count   0.30765    0.11333   2.715  0.00687 ** 
## category_code_LT01_5_count   0.96907    0.06101  15.884  < 2e-16 ***
## category_code_LT01_11_count  0.30689    0.12111   2.534  0.01159 *  
## category_code_LT01_12_count -0.15339    0.21095  -0.727  0.46749    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6344, Adjusted R-squared:  0.6299 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 0.629533910179342 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9999 -0.7762  0.0652  0.8210  3.4471 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.946102   0.087164 114.108  < 2e-16 ***
## category_code_LT01_1_count  0.334047   0.086855   3.846 0.000136 ***
## category_code_LT01_2_count  0.618389   0.089326   6.923 1.39e-11 ***
## category_code_LT01_3_count  0.308158   0.113391   2.718 0.006807 ** 
## category_code_LT01_5_count  0.965008   0.060844  15.860  < 2e-16 ***
## category_code_LT01_11_count 0.287485   0.118315   2.430 0.015463 *  
## category_code_LT01_13_count 0.009968   0.243160   0.041 0.967318    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.634,  Adjusted R-squared:  0.6295 
## F-statistic: 141.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 0.629683731515363 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9994 -0.7584  0.0660  0.8412  3.4451 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94806    0.08726 114.011  < 2e-16 ***
## category_code_LT01_1_count   0.32930    0.08671   3.798 0.000164 ***
## category_code_LT01_2_count   0.61450    0.08969   6.852  2.2e-11 ***
## category_code_LT01_3_count   0.31021    0.11346   2.734 0.006482 ** 
## category_code_LT01_5_count   0.96157    0.06130  15.687  < 2e-16 ***
## category_code_LT01_11_count  0.28617    0.11827   2.420 0.015898 *  
## category_code_LT01_14_count  0.14537    0.32479   0.448 0.654653    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6342, Adjusted R-squared:  0.6297 
## F-statistic: 141.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 0.629914941833 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9978 -0.7726  0.0651  0.8230  3.4487 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94444    0.08715 114.114  < 2e-16 ***
## category_code_LT01_1_count   0.34455    0.08701   3.960 8.61e-05 ***
## category_code_LT01_2_count   0.61981    0.08922   6.947 1.19e-11 ***
## category_code_LT01_3_count   0.31626    0.11390   2.777   0.0057 ** 
## category_code_LT01_5_count   0.96440    0.06077  15.869  < 2e-16 ***
## category_code_LT01_11_count  0.28726    0.11819   2.430   0.0154 *  
## category_code_LT01_15_count -0.53923    0.75716  -0.712   0.4767    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6344, Adjusted R-squared:  0.6299 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 0.629536129873302 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0000 -0.7726  0.0650  0.8303  3.4470 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94615    0.08717 114.102  < 2e-16 ***
## category_code_LT01_1_count   0.33486    0.08603   3.892 0.000113 ***
## category_code_LT01_2_count   0.61801    0.08958   6.899 1.62e-11 ***
## category_code_LT01_3_count   0.30738    0.11395   2.697 0.007227 ** 
## category_code_LT01_5_count   0.96508    0.06080  15.874  < 2e-16 ***
## category_code_LT01_11_count  0.28791    0.11831   2.433 0.015310 *  
## category_code_LT01_16_count  0.07919    1.16474   0.068 0.945823    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.634,  Adjusted R-squared:  0.6295 
## F-statistic: 141.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 0.625103295079344 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9951 -0.7764  0.0480  0.8305  3.4598 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93336    0.08753 113.486  < 2e-16 ***
## category_code_LT01_1_count   0.38118    0.08599   4.433 1.15e-05 ***
## category_code_LT01_2_count   0.72632    0.07951   9.135  < 2e-16 ***
## category_code_LT01_3_count   0.37673    0.11071   3.403 0.000722 ***
## category_code_LT01_5_count   0.97643    0.06138  15.908  < 2e-16 ***
## category_code_LT01_12_count -0.03682    0.20720  -0.178 0.859016    
## category_code_LT01_13_count  0.03002    0.24448   0.123 0.902320    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6296, Adjusted R-squared:  0.6251 
## F-statistic: 139.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 0.625301671179254 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9948 -0.7729  0.0412  0.8224  3.4575 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93565    0.08762 113.394  < 2e-16 ***
## category_code_LT01_1_count   0.37667    0.08574   4.393 1.37e-05 ***
## category_code_LT01_2_count   0.72196    0.07989   9.037  < 2e-16 ***
## category_code_LT01_3_count   0.37901    0.11076   3.422 0.000674 ***
## category_code_LT01_5_count   0.97271    0.06179  15.741  < 2e-16 ***
## category_code_LT01_12_count -0.04353    0.20756  -0.210 0.833962    
## category_code_LT01_14_count  0.17162    0.32724   0.524 0.600210    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6253 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 0.625496736906086 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9931 -0.7803  0.0668  0.8298  3.4616 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93156    0.08751 113.493  < 2e-16 ***
## category_code_LT01_1_count   0.39341    0.08615   4.567 6.27e-06 ***
## category_code_LT01_2_count   0.72856    0.07933   9.184  < 2e-16 ***
## category_code_LT01_3_count   0.38527    0.11126   3.463 0.000582 ***
## category_code_LT01_5_count   0.97622    0.06130  15.925  < 2e-16 ***
## category_code_LT01_12_count -0.04393    0.20733  -0.212 0.832283    
## category_code_LT01_15_count -0.55563    0.76255  -0.729 0.466566    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6255 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 0.625091941781429 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9951 -0.7778  0.0480  0.8303  3.4599 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93322    0.08753 113.481  < 2e-16 ***
## category_code_LT01_1_count   0.38275    0.08509   4.498 8.56e-06 ***
## category_code_LT01_2_count   0.72704    0.07962   9.132  < 2e-16 ***
## category_code_LT01_3_count   0.37696    0.11121   3.389 0.000757 ***
## category_code_LT01_5_count   0.97674    0.06133  15.926  < 2e-16 ***
## category_code_LT01_12_count -0.03667    0.20723  -0.177 0.859627    
## category_code_LT01_16_count -0.01693    1.17130  -0.014 0.988471    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6296, Adjusted R-squared:  0.6251 
## F-statistic: 139.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 0.625280594053302 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9939 -0.7689  0.0473  0.8287  3.4573 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93585    0.08763 113.385  < 2e-16 ***
## category_code_LT01_1_count   0.37285    0.08624   4.323 1.86e-05 ***
## category_code_LT01_2_count   0.71874    0.07915   9.081  < 2e-16 ***
## category_code_LT01_3_count   0.37774    0.11062   3.415 0.000691 ***
## category_code_LT01_5_count   0.97115    0.06158  15.771  < 2e-16 ***
## category_code_LT01_13_count  0.03127    0.24444   0.128 0.898250    
## category_code_LT01_14_count  0.16779    0.32661   0.514 0.607673    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6253 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 0.625464893313837 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9923 -0.7801  0.0715  0.8307  3.4614 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93178    0.08752 113.484  < 2e-16 ***
## category_code_LT01_1_count   0.39018    0.08666   4.502  8.4e-06 ***
## category_code_LT01_2_count   0.72555    0.07848   9.245  < 2e-16 ***
## category_code_LT01_3_count   0.38390    0.11112   3.455 0.000598 ***
## category_code_LT01_5_count   0.97475    0.06103  15.971  < 2e-16 ***
## category_code_LT01_13_count  0.01376    0.24538   0.056 0.955288    
## category_code_LT01_15_count -0.54389    0.76487  -0.711 0.477363    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6255 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 0.625079211648396 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9944 -0.7730  0.0482  0.8312  3.4597 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.933460   0.087537 113.477  < 2e-16 ***
## category_code_LT01_1_count   0.379272   0.085461   4.438 1.12e-05 ***
## category_code_LT01_2_count   0.724112   0.078763   9.194  < 2e-16 ***
## category_code_LT01_3_count   0.375832   0.111078   3.383 0.000773 ***
## category_code_LT01_5_count   0.975316   0.061061  15.973  < 2e-16 ***
## category_code_LT01_13_count  0.029598   0.244655   0.121 0.903757    
## category_code_LT01_16_count -0.007656   1.171938  -0.007 0.994790    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6296, Adjusted R-squared:  0.6251 
## F-statistic: 139.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 0.625660672497638 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9918 -0.7719  0.0593  0.8298  3.4591 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93407    0.08761 113.392  < 2e-16 ***
## category_code_LT01_1_count   0.38467    0.08627   4.459 1.02e-05 ***
## category_code_LT01_2_count   0.72059    0.07895   9.127  < 2e-16 ***
## category_code_LT01_3_count   0.38594    0.11114   3.473 0.000561 ***
## category_code_LT01_5_count   0.97078    0.06150  15.785  < 2e-16 ***
## category_code_LT01_14_count  0.16643    0.32642   0.510 0.610390    
## category_code_LT01_15_count -0.54643    0.76149  -0.718 0.473361    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6257 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 0.625268278673247 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9940 -0.7700  0.0465  0.8284  3.4574 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93573    0.08763 113.377  < 2e-16 ***
## category_code_LT01_1_count   0.37465    0.08528   4.393 1.37e-05 ***
## category_code_LT01_2_count   0.71932    0.07927   9.074  < 2e-16 ***
## category_code_LT01_3_count   0.37766    0.11109   3.399  0.00073 ***
## category_code_LT01_5_count   0.97148    0.06153  15.790  < 2e-16 ***
## category_code_LT01_14_count  0.16751    0.32702   0.512  0.60873    
## category_code_LT01_16_count  0.01783    1.17236   0.015  0.98787    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6253 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 0.625463769712387 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9923 -0.7800  0.0709  0.8306  3.4615 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93166    0.08752 113.483  < 2e-16 ***
## category_code_LT01_1_count   0.39082    0.08551   4.570 6.16e-06 ***
## category_code_LT01_2_count   0.72611    0.07856   9.243  < 2e-16 ***
## category_code_LT01_3_count   0.38444    0.11164   3.444 0.000623 ***
## category_code_LT01_5_count   0.97490    0.06098  15.986  < 2e-16 ***
## category_code_LT01_15_count -0.54909    0.76234  -0.720 0.471701    
## category_code_LT01_16_count -0.04793    1.17151  -0.041 0.967382    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6255 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 0.649125212334551 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9466 -0.7374  0.0372  0.8167  3.5032 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.92981    0.08473 117.192  < 2e-16 ***
## category_code_LT01_1_count  0.22439    0.08611   2.606  0.00944 ** 
## category_code_LT01_2_count  0.45276    0.08954   5.056 6.04e-07 ***
## category_code_LT01_4_count  0.49756    0.09991   4.980 8.81e-07 ***
## category_code_LT01_5_count  0.91164    0.06010  15.168  < 2e-16 ***
## category_code_LT01_6_count  0.28726    0.14880   1.931  0.05411 .  
## category_code_LT01_7_count  0.37202    0.14986   2.483  0.01338 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.334 on 491 degrees of freedom
## Multiple R-squared:  0.6534, Adjusted R-squared:  0.6491 
## F-statistic: 154.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 0.645003325320827 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9549 -0.7403  0.0774  0.8391  3.4890 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.92789    0.08525 116.460  < 2e-16 ***
## category_code_LT01_1_count  0.24391    0.08635   2.825  0.00492 ** 
## category_code_LT01_2_count  0.48171    0.08926   5.397 1.06e-07 ***
## category_code_LT01_4_count  0.54945    0.09829   5.590 3.77e-08 ***
## category_code_LT01_5_count  0.92633    0.06102  15.181  < 2e-16 ***
## category_code_LT01_6_count  0.28347    0.14975   1.893  0.05896 .  
## category_code_LT01_8_count -0.16615    0.26593  -0.625  0.53241    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.6493, Adjusted R-squared:  0.645 
## F-statistic: 151.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 0.646200575631786 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9426 -0.7192  0.0983  0.8729  3.5061 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.92405    0.08509 116.630  < 2e-16 ***
## category_code_LT01_1_count  0.23711    0.08624   2.749  0.00619 ** 
## category_code_LT01_2_count  0.46678    0.08978   5.199 2.95e-07 ***
## category_code_LT01_4_count  0.54121    0.09828   5.507 5.90e-08 ***
## category_code_LT01_5_count  0.91423    0.06041  15.134  < 2e-16 ***
## category_code_LT01_6_count  0.27153    0.14950   1.816  0.06993 .  
## category_code_LT01_9_count  0.31355    0.21882   1.433  0.15252    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.34 on 491 degrees of freedom
## Multiple R-squared:  0.6505, Adjusted R-squared:  0.6462 
## F-statistic: 152.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 0.645131247900668 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9322 -0.7576  0.0611  0.8733  3.4227 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90905    0.08828 112.242  < 2e-16 ***
## category_code_LT01_1_count   0.24430    0.08634   2.830  0.00485 ** 
## category_code_LT01_2_count   0.47778    0.08947   5.340 1.42e-07 ***
## category_code_LT01_4_count   0.54553    0.09839   5.544 4.83e-08 ***
## category_code_LT01_5_count   0.92086    0.06033  15.263  < 2e-16 ***
## category_code_LT01_6_count   0.26256    0.15135   1.735  0.08340 .  
## category_code_LT01_10_count  0.08297    0.11014   0.753  0.45162    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.6494, Adjusted R-squared:  0.6451 
## F-statistic: 151.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 0.646229936556032 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9550 -0.7703  0.0688  0.8332  3.4924 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93415    0.08523 116.550  < 2e-16 ***
## category_code_LT01_1_count   0.22265    0.08722   2.553   0.0110 *  
## category_code_LT01_2_count   0.43342    0.09537   4.545 6.93e-06 ***
## category_code_LT01_4_count   0.50976    0.10184   5.006 7.78e-07 ***
## category_code_LT01_5_count   0.91748    0.06028  15.221  < 2e-16 ***
## category_code_LT01_6_count   0.25809    0.15013   1.719   0.0862 .  
## category_code_LT01_11_count  0.16999    0.11747   1.447   0.1485    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.34 on 491 degrees of freedom
## Multiple R-squared:  0.6505, Adjusted R-squared:  0.6462 
## F-statistic: 152.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 0.644846884747332 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9507 -0.7603  0.0599  0.8714  3.4944 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92611    0.08524 116.449  < 2e-16 ***
## category_code_LT01_1_count   0.24628    0.08686   2.835  0.00476 ** 
## category_code_LT01_2_count   0.48688    0.08984   5.419 9.39e-08 ***
## category_code_LT01_4_count   0.55019    0.09834   5.595 3.67e-08 ***
## category_code_LT01_5_count   0.92297    0.06061  15.229  < 2e-16 ***
## category_code_LT01_6_count   0.28552    0.15030   1.900  0.05806 .  
## category_code_LT01_12_count -0.08441    0.20242  -0.417  0.67686    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.6491, Adjusted R-squared:  0.6448 
## F-statistic: 151.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 0.644722919919072 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9495 -0.7640  0.0859  0.8533  3.4965 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92642    0.08526 116.432  < 2e-16 ***
## category_code_LT01_1_count   0.24289    0.08717   2.786  0.00554 ** 
## category_code_LT01_2_count   0.48283    0.08936   5.404 1.02e-07 ***
## category_code_LT01_4_count   0.54947    0.09843   5.582 3.94e-08 ***
## category_code_LT01_5_count   0.92079    0.06041  15.243  < 2e-16 ***
## category_code_LT01_6_count   0.27955    0.14977   1.867  0.06255 .  
## category_code_LT01_13_count -0.01194    0.23831  -0.050  0.96006    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.649,  Adjusted R-squared:  0.6447 
## F-statistic: 151.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 0.644722503832821 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9495 -0.7631  0.0851  0.8577  3.4968 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92666    0.08536 116.287  < 2e-16 ***
## category_code_LT01_1_count   0.24189    0.08681   2.786  0.00554 ** 
## category_code_LT01_2_count   0.48239    0.08948   5.391 1.09e-07 ***
## category_code_LT01_4_count   0.54875    0.09895   5.546 4.79e-08 ***
## category_code_LT01_5_count   0.92036    0.06080  15.138  < 2e-16 ***
## category_code_LT01_6_count   0.28051    0.15061   1.863  0.06312 .  
## category_code_LT01_14_count  0.01413    0.32117   0.044  0.96493    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.649,  Adjusted R-squared:  0.6447 
## F-statistic: 151.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 0.644925665735199 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9482 -0.7404  0.0846  0.8510  3.4980 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92539    0.08525 116.427  < 2e-16 ***
## category_code_LT01_1_count   0.25018    0.08759   2.856  0.00447 ** 
## category_code_LT01_2_count   0.48457    0.08933   5.425 9.14e-08 ***
## category_code_LT01_4_count   0.54982    0.09830   5.593 3.71e-08 ***
## category_code_LT01_5_count   0.92041    0.06035  15.251  < 2e-16 ***
## category_code_LT01_6_count   0.28211    0.14972   1.884  0.06011 .  
## category_code_LT01_15_count -0.39260    0.73818  -0.532  0.59507    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.6492, Adjusted R-squared:  0.6449 
## F-statistic: 151.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 0.645000479475765 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9489 -0.7581  0.0715  0.8606  3.4977 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92670    0.08522 116.486  < 2e-16 ***
## category_code_LT01_1_count   0.24339    0.08633   2.819  0.00501 ** 
## category_code_LT01_2_count   0.47486    0.09012   5.269 2.06e-07 ***
## category_code_LT01_4_count   0.54962    0.09829   5.592 3.73e-08 ***
## category_code_LT01_5_count   0.91949    0.06037  15.230  < 2e-16 ***
## category_code_LT01_6_count   0.28828    0.15026   1.919  0.05562 .  
## category_code_LT01_16_count  0.70834    1.13952   0.622  0.53448    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.6493, Adjusted R-squared:  0.645 
## F-statistic: 151.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 0.646744314717797 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9684 -0.7283  0.0406  0.8353  3.4738 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93874    0.08497 116.972  < 2e-16 ***
## category_code_LT01_1_count  0.23740    0.08624   2.753  0.00613 ** 
## category_code_LT01_2_count  0.49192    0.08743   5.626 3.10e-08 ***
## category_code_LT01_4_count  0.53051    0.09879   5.370 1.22e-07 ***
## category_code_LT01_5_count  0.93028    0.06063  15.343  < 2e-16 ***
## category_code_LT01_7_count  0.36904    0.15040   2.454  0.01449 *  
## category_code_LT01_8_count -0.16620    0.26520  -0.627  0.53115    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.339 on 491 degrees of freedom
## Multiple R-squared:  0.651,  Adjusted R-squared:  0.6467 
## F-statistic: 152.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 0.647666953174414 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9564 -0.7188  0.0472  0.8078  3.4905 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93465    0.08484 117.094  < 2e-16 ***
## category_code_LT01_1_count  0.23161    0.08615   2.689  0.00742 ** 
## category_code_LT01_2_count  0.47853    0.08798   5.439 8.47e-08 ***
## category_code_LT01_4_count  0.52454    0.09876   5.311 1.65e-07 ***
## category_code_LT01_5_count  0.91877    0.06002  15.308  < 2e-16 ***
## category_code_LT01_7_count  0.34884    0.15073   2.314  0.02106 *  
## category_code_LT01_9_count  0.28390    0.21907   1.296  0.19559    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.337 on 491 degrees of freedom
## Multiple R-squared:  0.6519, Adjusted R-squared:  0.6477 
## F-statistic: 153.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 0.646979482858425 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9426 -0.7103  0.0279  0.8160  3.4006 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91721    0.08811 112.554  < 2e-16 ***
## category_code_LT01_1_count   0.23772    0.08620   2.758  0.00604 ** 
## category_code_LT01_2_count   0.48527    0.08782   5.526 5.34e-08 ***
## category_code_LT01_4_count   0.52533    0.09893   5.310 1.66e-07 ***
## category_code_LT01_5_count   0.92411    0.05991  15.424  < 2e-16 ***
## category_code_LT01_7_count   0.35652    0.15071   2.366  0.01839 *  
## category_code_LT01_10_count  0.09241    0.10890   0.849  0.39653    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.338 on 491 degrees of freedom
## Multiple R-squared:  0.6512, Adjusted R-squared:  0.647 
## F-statistic: 152.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 0.647390649642717 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9666 -0.7285  0.0456  0.8038  3.4790 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94253    0.08498 116.994  < 2e-16 ***
## category_code_LT01_1_count   0.22116    0.08707   2.540   0.0114 *  
## category_code_LT01_2_count   0.45376    0.09378   4.838 1.75e-06 ***
## category_code_LT01_4_count   0.50189    0.10181   4.930 1.13e-06 ***
## category_code_LT01_5_count   0.92208    0.05992  15.389  < 2e-16 ***
## category_code_LT01_7_count   0.32900    0.15371   2.140   0.0328 *  
## category_code_LT01_11_count  0.13582    0.11942   1.137   0.2560    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.337 on 491 degrees of freedom
## Multiple R-squared:  0.6516, Adjusted R-squared:  0.6474 
## F-statistic: 153.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 0.646494569495124 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9637 -0.7266  0.0496  0.8250  3.4803 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93709    0.08496 116.958  < 2e-16 ***
## category_code_LT01_1_count   0.23793    0.08682   2.740  0.00636 ** 
## category_code_LT01_2_count   0.49517    0.08829   5.608 3.41e-08 ***
## category_code_LT01_4_count   0.53114    0.09891   5.370 1.22e-07 ***
## category_code_LT01_5_count   0.92584    0.06026  15.363  < 2e-16 ***
## category_code_LT01_7_count   0.36575    0.15040   2.432  0.01538 *  
## category_code_LT01_12_count -0.04294    0.20112  -0.214  0.83101    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.339 on 491 degrees of freedom
## Multiple R-squared:  0.6508, Adjusted R-squared:  0.6465 
## F-statistic: 152.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 0.64655643726033 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9630 -0.7264  0.0427  0.8426  3.4813 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93688    0.08496 116.962  < 2e-16 ***
## category_code_LT01_1_count   0.23979    0.08693   2.758  0.00603 ** 
## category_code_LT01_2_count   0.49322    0.08747   5.639 2.89e-08 ***
## category_code_LT01_4_count   0.53098    0.09884   5.372 1.20e-07 ***
## category_code_LT01_5_count   0.92514    0.05997  15.426  < 2e-16 ***
## category_code_LT01_7_count   0.37186    0.15119   2.460  0.01425 *  
## category_code_LT01_13_count -0.08664    0.23888  -0.363  0.71699    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.339 on 491 degrees of freedom
## Multiple R-squared:  0.6508, Adjusted R-squared:  0.6466 
## F-statistic: 152.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 0.646525994210314 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9628 -0.7254  0.0418  0.8261  3.4810 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93579    0.08509 116.772  < 2e-16 ***
## category_code_LT01_1_count   0.23813    0.08659   2.750  0.00618 ** 
## category_code_LT01_2_count   0.49349    0.08751   5.639 2.88e-08 ***
## category_code_LT01_4_count   0.53267    0.09915   5.372 1.20e-07 ***
## category_code_LT01_5_count   0.92640    0.06028  15.369  < 2e-16 ***
## category_code_LT01_7_count   0.36868    0.15062   2.448  0.01472 *  
## category_code_LT01_14_count -0.09528    0.31892  -0.299  0.76526    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.339 on 491 degrees of freedom
## Multiple R-squared:  0.6508, Adjusted R-squared:  0.6465 
## F-statistic: 152.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 0.646553472200927 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9622 -0.7261  0.0424  0.8262  3.4824 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93649    0.08498 116.931  < 2e-16 ***
## category_code_LT01_1_count   0.24124    0.08758   2.755  0.00609 ** 
## category_code_LT01_2_count   0.49429    0.08758   5.644 2.82e-08 ***
## category_code_LT01_4_count   0.53121    0.09886   5.374 1.19e-07 ***
## category_code_LT01_5_count   0.92448    0.05995  15.421  < 2e-16 ***
## category_code_LT01_7_count   0.36348    0.15056   2.414  0.01614 *  
## category_code_LT01_15_count -0.26311    0.73709  -0.357  0.72127    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.339 on 491 degrees of freedom
## Multiple R-squared:  0.6508, Adjusted R-squared:  0.6466 
## F-statistic: 152.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 0.646626199599012 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9628 -0.7271  0.0560  0.8254  3.4820 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93755    0.08495 116.983  < 2e-16 ***
## category_code_LT01_1_count   0.23682    0.08624   2.746  0.00625 ** 
## category_code_LT01_2_count   0.48745    0.08810   5.533 5.13e-08 ***
## category_code_LT01_4_count   0.53118    0.09883   5.375 1.19e-07 ***
## category_code_LT01_5_count   0.92389    0.05996  15.409  < 2e-16 ***
## category_code_LT01_7_count   0.36699    0.15037   2.441  0.01502 *  
## category_code_LT01_16_count  0.54125    1.13227   0.478  0.63285    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.339 on 491 degrees of freedom
## Multiple R-squared:  0.6509, Adjusted R-squared:  0.6466 
## F-statistic: 152.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 0.644084688662526 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9629 -0.7330  0.0884  0.8636  3.4789 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93238    0.08529 116.453  < 2e-16 ***
## category_code_LT01_1_count  0.24895    0.08636   2.883  0.00411 ** 
## category_code_LT01_2_count  0.50250    0.08779   5.724 1.81e-08 ***
## category_code_LT01_4_count  0.57141    0.09720   5.879 7.65e-09 ***
## category_code_LT01_5_count  0.93146    0.06093  15.286  < 2e-16 ***
## category_code_LT01_8_count -0.15985    0.26622  -0.600  0.54849    
## category_code_LT01_9_count  0.33327    0.21943   1.519  0.12947    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.344 on 491 degrees of freedom
## Multiple R-squared:  0.6484, Adjusted R-squared:  0.6441 
## F-statistic: 150.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 0.643195840716046 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9455 -0.7385  0.0965  0.8684  3.3692 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91071    0.08854 111.932  < 2e-16 ***
## category_code_LT01_1_count   0.25657    0.08640   2.970  0.00313 ** 
## category_code_LT01_2_count   0.51070    0.08760   5.830 1.01e-08 ***
## category_code_LT01_4_count   0.57321    0.09740   5.885 7.38e-09 ***
## category_code_LT01_5_count   0.93767    0.06085  15.410  < 2e-16 ***
## category_code_LT01_8_count  -0.15308    0.26648  -0.574  0.56592    
## category_code_LT01_10_count  0.11337    0.10920   1.038  0.29972    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.345 on 491 degrees of freedom
## Multiple R-squared:  0.6475, Adjusted R-squared:  0.6432 
## F-statistic: 150.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 0.644288432392495 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9746 -0.7473  0.0680  0.8505  3.4664 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94286    0.08539 116.446  < 2e-16 ***
## category_code_LT01_1_count   0.23181    0.08741   2.652  0.00826 ** 
## category_code_LT01_2_count   0.46270    0.09410   4.917 1.20e-06 ***
## category_code_LT01_4_count   0.53435    0.10119   5.281 1.94e-07 ***
## category_code_LT01_5_count   0.93324    0.06083  15.341  < 2e-16 ***
## category_code_LT01_8_count  -0.13553    0.26608  -0.509  0.61073    
## category_code_LT01_11_count  0.18865    0.11724   1.609  0.10824    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6486, Adjusted R-squared:  0.6443 
## F-statistic:   151 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 0.642449387422355 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9710 -0.7528  0.0758  0.8382  3.4674 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93493    0.08547 116.238  < 2e-16 ***
## category_code_LT01_1_count   0.25690    0.08705   2.951  0.00332 ** 
## category_code_LT01_2_count   0.52331    0.08800   5.947 5.20e-09 ***
## category_code_LT01_4_count   0.58172    0.09730   5.979 4.33e-09 ***
## category_code_LT01_5_count   0.93953    0.06119  15.355  < 2e-16 ***
## category_code_LT01_8_count  -0.14424    0.26684  -0.541  0.58906    
## category_code_LT01_12_count -0.04544    0.20237  -0.225  0.82245    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6468, Adjusted R-squared:  0.6424 
## F-statistic: 149.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 0.64242728101654 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9704 -0.7509  0.0771  0.8440  3.4685 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93493    0.08548 116.231  < 2e-16 ***
## category_code_LT01_1_count   0.25636    0.08731   2.936  0.00348 ** 
## category_code_LT01_2_count   0.52102    0.08723   5.973 4.47e-09 ***
## category_code_LT01_4_count   0.58146    0.09732   5.975 4.43e-09 ***
## category_code_LT01_5_count   0.93860    0.06097  15.395  < 2e-16 ***
## category_code_LT01_8_count  -0.14867    0.26721  -0.556  0.57820    
## category_code_LT01_13_count -0.03390    0.23943  -0.142  0.88746    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6467, Adjusted R-squared:  0.6424 
## F-statistic: 149.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 0.642430043701705 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9702 -0.7499  0.0774  0.8536  3.4684 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93431    0.08561 116.045  < 2e-16 ***
## category_code_LT01_1_count   0.25594    0.08687   2.946  0.00337 ** 
## category_code_LT01_2_count   0.52118    0.08726   5.973 4.48e-09 ***
## category_code_LT01_4_count   0.58229    0.09766   5.962 4.76e-09 ***
## category_code_LT01_5_count   0.93921    0.06124  15.335  < 2e-16 ***
## category_code_LT01_8_count  -0.14582    0.26670  -0.547  0.58481    
## category_code_LT01_14_count -0.04945    0.32028  -0.154  0.87735    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6467, Adjusted R-squared:  0.6424 
## F-statistic: 149.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 0.642574826457957 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9692 -0.7489  0.0768  0.8364  3.4698 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93415    0.08548 116.222  < 2e-16 ***
## category_code_LT01_1_count   0.26175    0.08775   2.983    0.003 ** 
## category_code_LT01_2_count   0.52260    0.08726   5.989 4.09e-09 ***
## category_code_LT01_4_count   0.58162    0.09722   5.982 4.24e-09 ***
## category_code_LT01_5_count   0.93805    0.06090  15.403  < 2e-16 ***
## category_code_LT01_8_count  -0.14552    0.26664  -0.546    0.585    
## category_code_LT01_15_count -0.34939    0.74032  -0.472    0.637    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6469, Adjusted R-squared:  0.6426 
## F-statistic: 149.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 0.642578047093225 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9704 -0.7498  0.0737  0.8576  3.4688 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93547    0.08546 116.262  < 2e-16 ***
## category_code_LT01_1_count   0.25582    0.08649   2.958  0.00325 ** 
## category_code_LT01_2_count   0.51550    0.08781   5.870 8.02e-09 ***
## category_code_LT01_4_count   0.58191    0.09723   5.985 4.18e-09 ***
## category_code_LT01_5_count   0.93784    0.06091  15.398  < 2e-16 ***
## category_code_LT01_8_count  -0.15292    0.26699  -0.573  0.56707    
## category_code_LT01_16_count  0.54344    1.14020   0.477  0.63384    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6469, Adjusted R-squared:  0.6426 
## F-statistic: 149.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 0.644352520467406 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9375 -0.7154  0.0845  0.8840  3.4034 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91095    0.08838 112.135  < 2e-16 ***
## category_code_LT01_1_count   0.24925    0.08631   2.888  0.00405 ** 
## category_code_LT01_2_count   0.49619    0.08813   5.630 3.03e-08 ***
## category_code_LT01_4_count   0.56521    0.09739   5.803 1.17e-08 ***
## category_code_LT01_5_count   0.92579    0.06022  15.373  < 2e-16 ***
## category_code_LT01_9_count   0.30655    0.22078   1.389  0.16561    
## category_code_LT01_10_count  0.09382    0.10976   0.855  0.39312    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6486, Adjusted R-squared:  0.6444 
## F-statistic: 151.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 0.645577326828343 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9626 -0.7283  0.0831  0.8561  3.4831 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93874    0.08523 116.617  < 2e-16 ***
## category_code_LT01_1_count   0.22561    0.08725   2.586    0.010 *  
## category_code_LT01_2_count   0.44794    0.09449   4.741 2.79e-06 ***
## category_code_LT01_4_count   0.52640    0.10111   5.206 2.84e-07 ***
## category_code_LT01_5_count   0.92183    0.06017  15.319  < 2e-16 ***
## category_code_LT01_9_count   0.31336    0.21908   1.430    0.153    
## category_code_LT01_11_count  0.18255    0.11711   1.559    0.120    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.341 on 491 degrees of freedom
## Multiple R-squared:  0.6499, Adjusted R-squared:  0.6456 
## F-statistic: 151.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 0.643865537262317 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9586 -0.7237  0.0888  0.8723  3.4848 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93084    0.08529 116.442  < 2e-16 ***
## category_code_LT01_1_count   0.24976    0.08693   2.873  0.00424 ** 
## category_code_LT01_2_count   0.50606    0.08863   5.710 1.96e-08 ***
## category_code_LT01_4_count   0.57185    0.09730   5.877 7.72e-09 ***
## category_code_LT01_5_count   0.92743    0.06057  15.312  < 2e-16 ***
## category_code_LT01_9_count   0.32876    0.21938   1.499  0.13462    
## category_code_LT01_12_count -0.04868    0.20185  -0.241  0.80952    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.344 on 491 degrees of freedom
## Multiple R-squared:  0.6482, Adjusted R-squared:  0.6439 
## F-statistic: 150.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 0.643823349906131 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9577 -0.7221  0.0925  0.8756  3.4863 
## 
## Coefficients:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.9309592  0.0852944 116.432  < 2e-16 ***
## category_code_LT01_1_count   0.2473370  0.0871916   2.837  0.00475 ** 
## category_code_LT01_2_count   0.5031638  0.0878969   5.724 1.81e-08 ***
## category_code_LT01_4_count   0.5709377  0.0973405   5.865 8.24e-09 ***
## category_code_LT01_5_count   0.9259602  0.0603116  15.353  < 2e-16 ***
## category_code_LT01_9_count   0.3288464  0.2199505   1.495  0.13553    
## category_code_LT01_13_count -0.0001005  0.2391068   0.000  0.99966    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.344 on 491 degrees of freedom
## Multiple R-squared:  0.6481, Adjusted R-squared:  0.6438 
## F-statistic: 150.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 0.643868281239431 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9575 -0.7193  0.0914  0.8720  3.4858 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92974    0.08543 116.239  < 2e-16 ***
## category_code_LT01_1_count   0.24936    0.08672   2.875  0.00421 ** 
## category_code_LT01_2_count   0.50391    0.08786   5.735 1.70e-08 ***
## category_code_LT01_4_count   0.57314    0.09763   5.871 8.01e-09 ***
## category_code_LT01_5_count   0.92750    0.06058  15.311  < 2e-16 ***
## category_code_LT01_9_count   0.33204    0.21975   1.511  0.13144    
## category_code_LT01_14_count -0.07969    0.32016  -0.249  0.80355    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.344 on 491 degrees of freedom
## Multiple R-squared:  0.6482, Adjusted R-squared:  0.6439 
## F-statistic: 150.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 0.643955691672612 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9568 -0.7197  0.0926  0.8708  3.4872 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93017    0.08529 116.423  < 2e-16 ***
## category_code_LT01_1_count   0.25381    0.08765   2.896  0.00395 ** 
## category_code_LT01_2_count   0.50513    0.08792   5.745 1.61e-08 ***
## category_code_LT01_4_count   0.57171    0.09723   5.880 7.60e-09 ***
## category_code_LT01_5_count   0.92589    0.06025  15.366  < 2e-16 ***
## category_code_LT01_9_count   0.32577    0.21947   1.484  0.13836    
## category_code_LT01_15_count -0.31582    0.73927  -0.427  0.66942    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.344 on 491 degrees of freedom
## Multiple R-squared:  0.6483, Adjusted R-squared:  0.644 
## F-statistic: 150.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 0.643939698072111 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9577 -0.7208  0.0884  0.8814  3.4865 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93128    0.08528 116.456  < 2e-16 ***
## category_code_LT01_1_count   0.24830    0.08636   2.875  0.00422 ** 
## category_code_LT01_2_count   0.49905    0.08840   5.646 2.79e-08 ***
## category_code_LT01_4_count   0.57187    0.09725   5.881 7.56e-09 ***
## category_code_LT01_5_count   0.92550    0.06027  15.357  < 2e-16 ***
## category_code_LT01_9_count   0.32604    0.21947   1.486  0.13803    
## category_code_LT01_16_count  0.45546    1.13707   0.401  0.68892    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.344 on 491 degrees of freedom
## Multiple R-squared:  0.6482, Adjusted R-squared:  0.6439 
## F-statistic: 150.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 0.644782438682889 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9467 -0.7165  0.0319  0.8641  3.3802 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91874    0.08851 112.062  < 2e-16 ***
## category_code_LT01_1_count   0.23239    0.08732   2.661  0.00804 ** 
## category_code_LT01_2_count   0.45459    0.09440   4.816 1.96e-06 ***
## category_code_LT01_4_count   0.52727    0.10131   5.205 2.86e-07 ***
## category_code_LT01_5_count   0.92781    0.06007  15.446  < 2e-16 ***
## category_code_LT01_10_count  0.10582    0.10899   0.971  0.33208    
## category_code_LT01_11_count  0.18620    0.11719   1.589  0.11273    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.6491, Adjusted R-squared:  0.6448 
## F-statistic: 151.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 0.643014558011741 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9416 -0.7418  0.0995  0.8664  3.3750 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90924    0.08856 111.897  < 2e-16 ***
## category_code_LT01_1_count   0.25780    0.08697   2.964  0.00318 ** 
## category_code_LT01_2_count   0.51454    0.08839   5.821 1.06e-08 ***
## category_code_LT01_4_count   0.57374    0.09749   5.885 7.37e-09 ***
## category_code_LT01_5_count   0.93405    0.06045  15.450  < 2e-16 ***
## category_code_LT01_10_count  0.11304    0.10928   1.034  0.30145    
## category_code_LT01_12_count -0.05738    0.20225  -0.284  0.77674    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6473, Adjusted R-squared:  0.643 
## F-statistic: 150.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 0.642969771004937 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9407 -0.7481  0.1039  0.8718  3.3772 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90941    0.08857 111.885  < 2e-16 ***
## category_code_LT01_1_count   0.25655    0.08719   2.942  0.00341 ** 
## category_code_LT01_2_count   0.51161    0.08767   5.836 9.73e-09 ***
## category_code_LT01_4_count   0.57327    0.09751   5.879 7.62e-09 ***
## category_code_LT01_5_count   0.93260    0.06019  15.495  < 2e-16 ***
## category_code_LT01_10_count  0.11228    0.10925   1.028  0.30462    
## category_code_LT01_13_count -0.03284    0.23889  -0.137  0.89071    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6473, Adjusted R-squared:  0.643 
## F-statistic: 150.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 0.643065819583225 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9386 -0.7426  0.0920  0.8849  3.3687 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90574    0.08911 111.166  < 2e-16 ***
## category_code_LT01_1_count   0.25839    0.08683   2.976  0.00307 ** 
## category_code_LT01_2_count   0.51191    0.08763   5.842 9.42e-09 ***
## category_code_LT01_4_count   0.57577    0.09773   5.891 7.11e-09 ***
## category_code_LT01_5_count   0.93483    0.06049  15.454  < 2e-16 ***
## category_code_LT01_10_count  0.12110    0.11177   1.084  0.27911    
## category_code_LT01_14_count -0.12728    0.32753  -0.389  0.69772    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6474, Adjusted R-squared:  0.6431 
## F-statistic: 150.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 0.643185358731358 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9384 -0.7402  0.0961  0.8666  3.3746 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90748    0.08861 111.812  < 2e-16 ***
## category_code_LT01_1_count   0.26347    0.08769   3.005  0.00279 ** 
## category_code_LT01_2_count   0.51318    0.08767   5.854 8.80e-09 ***
## category_code_LT01_4_count   0.57329    0.09741   5.886 7.35e-09 ***
## category_code_LT01_5_count   0.93211    0.06014  15.500  < 2e-16 ***
## category_code_LT01_10_count  0.11688    0.10954   1.067  0.28649    
## category_code_LT01_15_count -0.41692    0.74217  -0.562  0.57454    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.345 on 491 degrees of freedom
## Multiple R-squared:  0.6475, Adjusted R-squared:  0.6432 
## F-statistic: 150.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 0.643077809736378 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9411 -0.7477  0.1050  0.8772  3.3795 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91031    0.08855 111.915  < 2e-16 ***
## category_code_LT01_1_count   0.25583    0.08640   2.961  0.00321 ** 
## category_code_LT01_2_count   0.50703    0.08822   5.747 1.59e-08 ***
## category_code_LT01_4_count   0.57373    0.09745   5.888 7.27e-09 ***
## category_code_LT01_5_count   0.93180    0.06016  15.489  < 2e-16 ***
## category_code_LT01_10_count  0.11014    0.10927   1.008  0.31397    
## category_code_LT01_16_count  0.46607    1.13868   0.409  0.68250    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6474, Adjusted R-squared:  0.6431 
## F-statistic: 150.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 0.644378285164627 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9729 -0.7472  0.0491  0.8372  3.4687 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94206    0.08535 116.490  < 2e-16 ***
## category_code_LT01_1_count   0.23460    0.08763   2.677  0.00767 ** 
## category_code_LT01_2_count   0.46514    0.09418   4.939 1.08e-06 ***
## category_code_LT01_4_count   0.53181    0.10120   5.255 2.21e-07 ***
## category_code_LT01_5_count   0.93192    0.06036  15.440  < 2e-16 ***
## category_code_LT01_11_count  0.20666    0.12018   1.720  0.08614 .  
## category_code_LT01_12_count -0.12811    0.20686  -0.619  0.53599    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6487, Adjusted R-squared:  0.6444 
## F-statistic: 151.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 0.644115522659438 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9702 -0.7415  0.0503  0.8443  3.4727 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94156    0.08538 116.438  < 2e-16 ***
## category_code_LT01_1_count   0.23185    0.08813   2.631  0.00878 ** 
## category_code_LT01_2_count   0.46291    0.09415   4.917 1.20e-06 ***
## category_code_LT01_4_count   0.53396    0.10126   5.273 2.01e-07 ***
## category_code_LT01_5_count   0.92874    0.06015  15.440  < 2e-16 ***
## category_code_LT01_11_count  0.19053    0.11726   1.625  0.10483    
## category_code_LT01_13_count -0.03436    0.23846  -0.144  0.88550    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.344 on 491 degrees of freedom
## Multiple R-squared:  0.6484, Adjusted R-squared:  0.6441 
## F-statistic: 150.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 0.644116112108924 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9701 -0.7426  0.0644  0.8416  3.4725 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94098    0.08551 116.252  < 2e-16 ***
## category_code_LT01_1_count   0.23144    0.08778   2.636  0.00864 ** 
## category_code_LT01_2_count   0.46319    0.09421   4.917 1.20e-06 ***
## category_code_LT01_4_count   0.53485    0.10164   5.262 2.13e-07 ***
## category_code_LT01_5_count   0.92941    0.06047  15.370  < 2e-16 ***
## category_code_LT01_11_count  0.19000    0.11723   1.621  0.10573    
## category_code_LT01_14_count -0.04693    0.31952  -0.147  0.88330    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.344 on 491 degrees of freedom
## Multiple R-squared:  0.6484, Adjusted R-squared:  0.6441 
## F-statistic: 150.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 0.644284087461536 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9691 -0.7334  0.0584  0.8411  3.4740 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94077    0.08538 116.436  < 2e-16 ***
## category_code_LT01_1_count   0.23764    0.08859   2.682  0.00756 ** 
## category_code_LT01_2_count   0.46442    0.09417   4.932 1.12e-06 ***
## category_code_LT01_4_count   0.53403    0.10118   5.278 1.97e-07 ***
## category_code_LT01_5_count   0.92827    0.06011  15.444  < 2e-16 ***
## category_code_LT01_11_count  0.19113    0.11722   1.631  0.10363    
## category_code_LT01_15_count -0.37185    0.73863  -0.503  0.61489    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6486, Adjusted R-squared:  0.6443 
## F-statistic:   151 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 0.64424847177089 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9700 -0.7385  0.0588  0.8579  3.4732 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94202    0.08536 116.467  < 2e-16 ***
## category_code_LT01_1_count   0.23121    0.08739   2.646  0.00841 ** 
## category_code_LT01_2_count   0.45776    0.09471   4.833 1.80e-06 ***
## category_code_LT01_4_count   0.53440    0.10120   5.280 1.94e-07 ***
## category_code_LT01_5_count   0.92786    0.06012  15.433  < 2e-16 ***
## category_code_LT01_11_count  0.19026    0.11721   1.623  0.10517    
## category_code_LT01_16_count  0.51342    1.13600   0.452  0.65151    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6485, Adjusted R-squared:  0.6442 
## F-statistic:   151 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 0.642244682179923 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9663 -0.7657  0.0777  0.8441  3.4741 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93350    0.08547 116.227  < 2e-16 ***
## category_code_LT01_1_count   0.25679    0.08783   2.924  0.00362 ** 
## category_code_LT01_2_count   0.52422    0.08807   5.953 5.03e-09 ***
## category_code_LT01_4_count   0.58167    0.09741   5.972 4.51e-09 ***
## category_code_LT01_5_count   0.93480    0.06055  15.438  < 2e-16 ***
## category_code_LT01_12_count -0.04906    0.20232  -0.242  0.80850    
## category_code_LT01_13_count -0.02516    0.23903  -0.105  0.91620    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6466, Adjusted R-squared:  0.6422 
## F-statistic: 149.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 0.642252333208346 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9662 -0.7566  0.0775  0.8514  3.4739 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93290    0.08559 116.049  < 2e-16 ***
## category_code_LT01_1_count   0.25670    0.08738   2.938  0.00346 ** 
## category_code_LT01_2_count   0.52436    0.08807   5.954 4.99e-09 ***
## category_code_LT01_4_count   0.58256    0.09774   5.961 4.81e-09 ***
## category_code_LT01_5_count   0.93549    0.06083  15.380  < 2e-16 ***
## category_code_LT01_12_count -0.04747    0.20265  -0.234  0.81489    
## category_code_LT01_14_count -0.04714    0.32089  -0.147  0.88326    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6466, Adjusted R-squared:  0.6423 
## F-statistic: 149.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 0.642408891992482 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9653 -0.7529  0.0767  0.8370  3.4752 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93266    0.08546 116.223  < 2e-16 ***
## category_code_LT01_1_count   0.26310    0.08839   2.977  0.00306 ** 
## category_code_LT01_2_count   0.52623    0.08813   5.971 4.52e-09 ***
## category_code_LT01_4_count   0.58210    0.09732   5.982 4.26e-09 ***
## category_code_LT01_5_count   0.93456    0.06050  15.446  < 2e-16 ***
## category_code_LT01_12_count -0.05352    0.20246  -0.264  0.79161    
## category_code_LT01_15_count -0.36049    0.74118  -0.486  0.62692    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6467, Adjusted R-squared:  0.6424 
## F-statistic: 149.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 0.642380257832261 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9662 -0.7579  0.0784  0.8530  3.4745 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93393    0.08545 116.259  < 2e-16 ***
## category_code_LT01_1_count   0.25651    0.08705   2.947  0.00336 ** 
## category_code_LT01_2_count   0.51911    0.08867   5.855 8.76e-09 ***
## category_code_LT01_4_count   0.58217    0.09733   5.982 4.26e-09 ***
## category_code_LT01_5_count   0.93398    0.06052  15.432  < 2e-16 ***
## category_code_LT01_12_count -0.04800    0.20229  -0.237  0.81253    
## category_code_LT01_16_count  0.50587    1.13908   0.444  0.65716    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6467, Adjusted R-squared:  0.6424 
## F-statistic: 149.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 0.642221128243848 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9654 -0.7528  0.0786  0.8598  3.4752 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93283    0.08560 116.033  < 2e-16 ***
## category_code_LT01_1_count   0.25576    0.08768   2.917   0.0037 ** 
## category_code_LT01_2_count   0.52193    0.08733   5.976 4.39e-09 ***
## category_code_LT01_4_count   0.58226    0.09778   5.955 4.96e-09 ***
## category_code_LT01_5_count   0.93438    0.06060  15.420  < 2e-16 ***
## category_code_LT01_13_count -0.02623    0.23907  -0.110   0.9127    
## category_code_LT01_14_count -0.05213    0.32040  -0.163   0.8708    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6465, Adjusted R-squared:  0.6422 
## F-statistic: 149.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 0.642374550928851 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9644 -0.7507  0.0787  0.8421  3.4766 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93263    0.08547 116.208  < 2e-16 ***
## category_code_LT01_1_count   0.26226    0.08873   2.956  0.00327 ** 
## category_code_LT01_2_count   0.52351    0.08735   5.993 3.98e-09 ***
## category_code_LT01_4_count   0.58172    0.09734   5.976 4.39e-09 ***
## category_code_LT01_5_count   0.93326    0.06023  15.494  < 2e-16 ***
## category_code_LT01_13_count -0.03618    0.23998  -0.151  0.88022    
## category_code_LT01_15_count -0.36209    0.74358  -0.487  0.62651    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6467, Adjusted R-squared:  0.6424 
## F-statistic: 149.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 0.642345269524231 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9653 -0.7629  0.0793  0.8618  3.4759 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93395    0.08546 116.246  < 2e-16 ***
## category_code_LT01_1_count   0.25520    0.08727   2.924  0.00361 ** 
## category_code_LT01_2_count   0.51653    0.08790   5.876 7.74e-09 ***
## category_code_LT01_4_count   0.58164    0.09734   5.975 4.42e-09 ***
## category_code_LT01_5_count   0.93271    0.06025  15.481  < 2e-16 ***
## category_code_LT01_13_count -0.02174    0.23915  -0.091  0.92759    
## category_code_LT01_16_count  0.50577    1.13977   0.444  0.65742    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6467, Adjusted R-squared:  0.6423 
## F-statistic: 149.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 0.642377826722176 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9643 -0.7463  0.0784  0.8517  3.4764 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93202    0.08560 116.028  < 2e-16 ***
## category_code_LT01_1_count   0.26166    0.08815   2.968  0.00314 ** 
## category_code_LT01_2_count   0.52362    0.08736   5.994 3.98e-09 ***
## category_code_LT01_4_count   0.58260    0.09768   5.964 4.70e-09 ***
## category_code_LT01_5_count   0.93402    0.06055  15.427  < 2e-16 ***
## category_code_LT01_14_count -0.05285    0.32030  -0.165  0.86901    
## category_code_LT01_15_count -0.35297    0.74053  -0.477  0.63383    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6467, Adjusted R-squared:  0.6424 
## F-statistic: 149.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 0.642353035570763 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9653 -0.7450  0.0768  0.8632  3.4757 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93338    0.08559 116.063  < 2e-16 ***
## category_code_LT01_1_count   0.25526    0.08686   2.939  0.00345 ** 
## category_code_LT01_2_count   0.51681    0.08794   5.877 7.72e-09 ***
## category_code_LT01_4_count   0.58253    0.09768   5.963 4.73e-09 ***
## category_code_LT01_5_count   0.93343    0.06057  15.411  < 2e-16 ***
## category_code_LT01_14_count -0.04413    0.32074  -0.138  0.89063    
## category_code_LT01_16_count  0.50126    1.14059   0.439  0.66051    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6467, Adjusted R-squared:  0.6424 
## F-statistic: 149.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 0.642494413231076 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9643 -0.7498  0.0752  0.8520  3.4770 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93315    0.08545 116.240  < 2e-16 ***
## category_code_LT01_1_count   0.26105    0.08774   2.975  0.00307 ** 
## category_code_LT01_2_count   0.51833    0.08793   5.895 6.99e-09 ***
## category_code_LT01_4_count   0.58198    0.09725   5.984 4.19e-09 ***
## category_code_LT01_5_count   0.93239    0.06020  15.488  < 2e-16 ***
## category_code_LT01_15_count -0.34195    0.74074  -0.462  0.64455    
## category_code_LT01_16_count  0.49316    1.13935   0.433  0.66532    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6468, Adjusted R-squared:  0.6425 
## F-statistic: 149.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 0.631773506343725 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9926 -0.7776  0.0329  0.9056  3.4551 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93803    0.08682 114.464  < 2e-16 ***
## category_code_LT01_1_count  0.36929    0.08318   4.440 1.11e-05 ***
## category_code_LT01_2_count  0.68120    0.07863   8.664  < 2e-16 ***
## category_code_LT01_5_count  0.96621    0.06144  15.726  < 2e-16 ***
## category_code_LT01_6_count  0.41719    0.15034   2.775 0.005732 ** 
## category_code_LT01_7_count  0.53084    0.15022   3.534 0.000449 ***
## category_code_LT01_8_count -0.19098    0.27097  -0.705 0.481271    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6362, Adjusted R-squared:  0.6318 
## F-statistic: 143.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 0.632814602214101 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9795 -0.7836  0.0444  0.8708  3.4594 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93375    0.08669 114.591  < 2e-16 ***
## category_code_LT01_1_count  0.36197    0.08313   4.354 1.63e-05 ***
## category_code_LT01_2_count  0.66619    0.07940   8.391 5.18e-16 ***
## category_code_LT01_5_count  0.95345    0.06086  15.667  < 2e-16 ***
## category_code_LT01_6_count  0.40315    0.15018   2.684 0.007511 ** 
## category_code_LT01_7_count  0.50694    0.15068   3.364 0.000827 ***
## category_code_LT01_9_count  0.30751    0.22366   1.375 0.169795    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.365 on 491 degrees of freedom
## Multiple R-squared:  0.6372, Adjusted R-squared:  0.6328 
## F-statistic: 143.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 0.631775716795183 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9698 -0.7762  0.0384  0.9248  3.4736 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91956    0.08999 110.234  < 2e-16 ***
## category_code_LT01_1_count   0.36931    0.08318   4.440 1.11e-05 ***
## category_code_LT01_2_count   0.67760    0.07892   8.585  < 2e-16 ***
## category_code_LT01_5_count   0.95998    0.06077  15.797  < 2e-16 ***
## category_code_LT01_6_count   0.39567    0.15220   2.600 0.009612 ** 
## category_code_LT01_7_count   0.51814    0.15073   3.437 0.000637 ***
## category_code_LT01_10_count  0.07952    0.11249   0.707 0.479973    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6362, Adjusted R-squared:  0.6318 
## F-statistic: 143.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 0.63438303709401 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9910 -0.7622  0.0336  0.8717  3.4472 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94594    0.08661 114.830  < 2e-16 ***
## category_code_LT01_1_count   0.32997    0.08496   3.884 0.000117 ***
## category_code_LT01_2_count   0.59757    0.08912   6.705 5.54e-11 ***
## category_code_LT01_5_count   0.95246    0.06066  15.701  < 2e-16 ***
## category_code_LT01_6_count   0.36953    0.15125   2.443 0.014913 *  
## category_code_LT01_7_count   0.44720    0.15490   2.887 0.004062 ** 
## category_code_LT01_11_count  0.23838    0.11912   2.001 0.045923 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.362 on 491 degrees of freedom
## Multiple R-squared:  0.6388, Adjusted R-squared:  0.6344 
## F-statistic: 144.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 0.631452173382581 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9874 -0.7787  0.0353  0.9070  3.4570 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93614    0.08683 114.429  < 2e-16 ***
## category_code_LT01_1_count   0.37041    0.08385   4.417 1.23e-05 ***
## category_code_LT01_2_count   0.68570    0.07949   8.626  < 2e-16 ***
## category_code_LT01_5_count   0.96136    0.06108  15.740  < 2e-16 ***
## category_code_LT01_6_count   0.41676    0.15100   2.760 0.005996 ** 
## category_code_LT01_7_count   0.52728    0.15022   3.510 0.000489 ***
## category_code_LT01_12_count -0.05384    0.20615  -0.261 0.794075    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6359, Adjusted R-squared:  0.6315 
## F-statistic: 142.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 0.631426128739117 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9867 -0.7742  0.0387  0.9087  3.4569 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93623    0.08683 114.427  < 2e-16 ***
## category_code_LT01_1_count   0.36988    0.08408   4.399 1.33e-05 ***
## category_code_LT01_2_count   0.68331    0.07872   8.681  < 2e-16 ***
## category_code_LT01_5_count   0.96021    0.06083  15.784  < 2e-16 ***
## category_code_LT01_6_count   0.41225    0.15034   2.742 0.006327 ** 
## category_code_LT01_7_count   0.53057    0.15115   3.510 0.000489 ***
## category_code_LT01_13_count -0.04466    0.24396  -0.183 0.854836    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6359, Adjusted R-squared:  0.6314 
## F-statistic: 142.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 0.631515820832025 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9860 -0.7912  0.0407  0.9162  3.4551 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93803    0.08692 114.329  < 2e-16 ***
## category_code_LT01_1_count   0.36308    0.08399   4.323 1.86e-05 ***
## category_code_LT01_2_count   0.67872    0.07927   8.562  < 2e-16 ***
## category_code_LT01_5_count   0.95665    0.06133  15.599  < 2e-16 ***
## category_code_LT01_6_count   0.41844    0.15093   2.772 0.005776 ** 
## category_code_LT01_7_count   0.52303    0.15064   3.472 0.000562 ***
## category_code_LT01_14_count  0.12752    0.32598   0.391 0.695828    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.636,  Adjusted R-squared:  0.6315 
## F-statistic:   143 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 0.631468253857865 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9859 -0.7749  0.0421  0.9047  3.4574 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93573    0.08685 114.398  < 2e-16 ***
## category_code_LT01_1_count   0.37248    0.08473   4.396 1.35e-05 ***
## category_code_LT01_2_count   0.68425    0.07881   8.682  < 2e-16 ***
## category_code_LT01_5_count   0.95978    0.06079  15.788  < 2e-16 ***
## category_code_LT01_6_count   0.41440    0.15036   2.756 0.006070 ** 
## category_code_LT01_7_count   0.52544    0.15037   3.494 0.000518 ***
## category_code_LT01_15_count -0.22538    0.75278  -0.299 0.764770    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6359, Adjusted R-squared:  0.6315 
## F-statistic: 142.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 0.631695092464362 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9859 -0.7741  0.0425  0.9116  3.4565 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93662    0.08680 114.476  < 2e-16 ***
## category_code_LT01_1_count   0.36878    0.08317   4.434 1.14e-05 ***
## category_code_LT01_2_count   0.67466    0.07964   8.471 2.84e-16 ***
## category_code_LT01_5_count   0.95859    0.06081  15.765  < 2e-16 ***
## category_code_LT01_6_count   0.42174    0.15089   2.795 0.005394 ** 
## category_code_LT01_7_count   0.52886    0.15018   3.522 0.000469 ***
## category_code_LT01_16_count  0.72685    1.16078   0.626 0.531491    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6361, Adjusted R-squared:  0.6317 
## F-statistic: 143.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 0.624666398470587 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9934 -0.7980  0.0709  0.9539  3.4623 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.93084    0.08767 113.282  < 2e-16 ***
## category_code_LT01_1_count  0.40850    0.08300   4.922 1.17e-06 ***
## category_code_LT01_2_count  0.73685    0.07734   9.528  < 2e-16 ***
## category_code_LT01_5_count  0.97761    0.06197  15.776  < 2e-16 ***
## category_code_LT01_6_count  0.41244    0.15194   2.714  0.00687 ** 
## category_code_LT01_8_count -0.17599    0.27358  -0.643  0.52033    
## category_code_LT01_9_count  0.38688    0.22513   1.718  0.08634 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6292, Adjusted R-squared:  0.6247 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 0.623196186737118 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9780 -0.8159  0.0214  0.9566  3.4835 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90969    0.09099 108.909  < 2e-16 ***
## category_code_LT01_1_count   0.41909    0.08299   5.050 6.25e-07 ***
## category_code_LT01_2_count   0.75216    0.07670   9.807  < 2e-16 ***
## category_code_LT01_5_count   0.98601    0.06189  15.932  < 2e-16 ***
## category_code_LT01_6_count   0.39979    0.15407   2.595  0.00974 ** 
## category_code_LT01_8_count  -0.16612    0.27402  -0.606  0.54465    
## category_code_LT01_10_count  0.11483    0.11337   1.013  0.31163    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6277, Adjusted R-squared:  0.6232 
## F-statistic:   138 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 0.628377246628856 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0055 -0.7960  0.0495  0.8646  3.4456 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94753    0.08735 113.881  < 2e-16 ***
## category_code_LT01_1_count   0.35605    0.08530   4.174 3.54e-05 ***
## category_code_LT01_2_count   0.62875    0.08918   7.050 6.09e-12 ***
## category_code_LT01_5_count   0.97104    0.06170  15.739  < 2e-16 ***
## category_code_LT01_6_count   0.36330    0.15260   2.381  0.01766 *  
## category_code_LT01_8_count  -0.14003    0.27219  -0.514  0.60716    
## category_code_LT01_11_count  0.32585    0.11604   2.808  0.00518 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 491 degrees of freedom
## Multiple R-squared:  0.6329, Adjusted R-squared:  0.6284 
## F-statistic: 141.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 0.622461089440733 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0030 -0.8069  0.0230  0.9515  3.4596 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93357    0.08791 112.997  < 2e-16 ***
## category_code_LT01_1_count   0.42062    0.08373   5.024 7.11e-07 ***
## category_code_LT01_2_count   0.76459    0.07710   9.916  < 2e-16 ***
## category_code_LT01_5_count   0.98760    0.06221  15.876  < 2e-16 ***
## category_code_LT01_6_count   0.42863    0.15292   2.803  0.00526 ** 
## category_code_LT01_8_count  -0.15864    0.27437  -0.578  0.56339    
## category_code_LT01_12_count -0.05437    0.20875  -0.260  0.79462    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.627,  Adjusted R-squared:  0.6225 
## F-statistic: 137.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 0.622430865212944 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0020 -0.8045  0.0340  0.9389  3.4592 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93393    0.08791 112.999  < 2e-16 ***
## category_code_LT01_1_count   0.41550    0.08425   4.932 1.12e-06 ***
## category_code_LT01_2_count   0.76053    0.07645   9.948  < 2e-16 ***
## category_code_LT01_5_count   0.98556    0.06205  15.884  < 2e-16 ***
## category_code_LT01_6_count   0.42535    0.15226   2.794  0.00541 ** 
## category_code_LT01_8_count  -0.15803    0.27477  -0.575  0.56546    
## category_code_LT01_13_count  0.04153    0.24586   0.169  0.86594    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.627,  Adjusted R-squared:  0.6224 
## F-statistic: 137.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 0.622742533286341 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0013 -0.8070  0.0344  0.9506  3.4564 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93671    0.08798 112.939  < 2e-16 ***
## category_code_LT01_1_count   0.40945    0.08401   4.874 1.48e-06 ***
## category_code_LT01_2_count   0.75368    0.07711   9.774  < 2e-16 ***
## category_code_LT01_5_count   0.98055    0.06251  15.687  < 2e-16 ***
## category_code_LT01_6_count   0.43412    0.15281   2.841  0.00469 ** 
## category_code_LT01_8_count  -0.16387    0.27418  -0.598  0.55034    
## category_code_LT01_14_count  0.21674    0.32893   0.659  0.51025    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6273, Adjusted R-squared:  0.6227 
## F-statistic: 137.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 0.622565862485016 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0011 -0.7958  0.0357  0.9506  3.4603 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93286    0.08792 112.979  < 2e-16 ***
## category_code_LT01_1_count   0.42494    0.08451   5.028 6.96e-07 ***
## category_code_LT01_2_count   0.76350    0.07632  10.003  < 2e-16 ***
## category_code_LT01_5_count   0.98593    0.06194  15.917  < 2e-16 ***
## category_code_LT01_6_count   0.42698    0.15227   2.804  0.00525 ** 
## category_code_LT01_8_count  -0.16023    0.27421  -0.584  0.55925    
## category_code_LT01_15_count -0.34386    0.76103  -0.452  0.65159    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6271, Adjusted R-squared:  0.6226 
## F-statistic: 137.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 0.62268764558517 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0020 -0.7921  0.0262  0.9506  3.4590 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93412    0.08788 113.041  < 2e-16 ***
## category_code_LT01_1_count   0.41919    0.08307   5.046 6.35e-07 ***
## category_code_LT01_2_count   0.75390    0.07724   9.760  < 2e-16 ***
## category_code_LT01_5_count   0.98530    0.06195  15.906  < 2e-16 ***
## category_code_LT01_6_count   0.43363    0.15287   2.837  0.00475 ** 
## category_code_LT01_8_count  -0.17010    0.27459  -0.619  0.53590    
## category_code_LT01_16_count  0.70860    1.17660   0.602  0.54729    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6272, Adjusted R-squared:  0.6227 
## F-statistic: 137.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 0.624853440900703 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9687 -0.7942  0.0706  0.9597  3.4831 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91009    0.09078 109.171  < 2e-16 ***
## category_code_LT01_1_count   0.40828    0.08296   4.921 1.17e-06 ***
## category_code_LT01_2_count   0.73185    0.07767   9.423  < 2e-16 ***
## category_code_LT01_5_count   0.97196    0.06127  15.864  < 2e-16 ***
## category_code_LT01_6_count   0.38908    0.15369   2.532   0.0117 *  
## category_code_LT01_9_count   0.36085    0.22650   1.593   0.1118    
## category_code_LT01_10_count  0.09243    0.11387   0.812   0.4174    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6294, Adjusted R-squared:  0.6249 
## F-statistic:   139 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 0.630002336187957 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9924 -0.7983  0.0740  0.8543  3.4500 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94319    0.08716 114.085  < 2e-16 ***
## category_code_LT01_1_count   0.34763    0.08516   4.082 5.21e-05 ***
## category_code_LT01_2_count   0.61071    0.08974   6.805 2.95e-11 ***
## category_code_LT01_5_count   0.95849    0.06104  15.703  < 2e-16 ***
## category_code_LT01_6_count   0.35025    0.15224   2.301  0.02183 *  
## category_code_LT01_9_count   0.34825    0.22375   1.556  0.12026    
## category_code_LT01_11_count  0.31748    0.11592   2.739  0.00639 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:   0.63 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 0.624406895191087 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9887 -0.7983  0.0736  0.9598  3.4640 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92914    0.08767 113.256  < 2e-16 ***
## category_code_LT01_1_count   0.40971    0.08366   4.897 1.32e-06 ***
## category_code_LT01_2_count   0.74121    0.07822   9.476  < 2e-16 ***
## category_code_LT01_5_count   0.97333    0.06159  15.803  < 2e-16 ***
## category_code_LT01_6_count   0.41265    0.15260   2.704  0.00708 ** 
## category_code_LT01_9_count   0.38198    0.22509   1.697  0.09033 .  
## category_code_LT01_12_count -0.05673    0.20811  -0.273  0.78529    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6289, Adjusted R-squared:  0.6244 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 0.624428397954583 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9873 -0.7952  0.0845  0.9443  3.4635 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92962    0.08767 113.266  < 2e-16 ***
## category_code_LT01_1_count   0.40227    0.08419   4.778 2.34e-06 ***
## category_code_LT01_2_count   0.73576    0.07766   9.474  < 2e-16 ***
## category_code_LT01_5_count   0.97070    0.06139  15.813  < 2e-16 ***
## category_code_LT01_6_count   0.40959    0.15191   2.696  0.00725 ** 
## category_code_LT01_9_count   0.38708    0.22560   1.716  0.08683 .  
## category_code_LT01_13_count  0.07851    0.24531   0.320  0.74909    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6244 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 0.624569078187665 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9871 -0.7960  0.0771  0.9532  3.4614 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93177    0.08776 113.168  < 2e-16 ***
## category_code_LT01_1_count   0.40016    0.08390   4.769 2.44e-06 ***
## category_code_LT01_2_count   0.73218    0.07809   9.376  < 2e-16 ***
## category_code_LT01_5_count   0.96728    0.06185  15.639  < 2e-16 ***
## category_code_LT01_6_count   0.41639    0.15254   2.730  0.00657 ** 
## category_code_LT01_9_count   0.37393    0.22558   1.658  0.09803 .  
## category_code_LT01_14_count  0.17601    0.32886   0.535  0.59275    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6246 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 0.624472163776059 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9869 -0.7914  0.0796  0.9345  3.4646 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92857    0.08768 113.235  < 2e-16 ***
## category_code_LT01_1_count   0.41314    0.08448   4.891 1.36e-06 ***
## category_code_LT01_2_count   0.73993    0.07748   9.550  < 2e-16 ***
## category_code_LT01_5_count   0.97162    0.06130  15.850  < 2e-16 ***
## category_code_LT01_6_count   0.41064    0.15195   2.702  0.00712 ** 
## category_code_LT01_9_count   0.37922    0.22520   1.684  0.09283 .  
## category_code_LT01_15_count -0.30348    0.75952  -0.400  0.68965    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 0.624549273635598 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9874 -0.7942  0.0849  0.9594  3.4636 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92960    0.08765 113.287  < 2e-16 ***
## category_code_LT01_1_count   0.40795    0.08300   4.915 1.21e-06 ***
## category_code_LT01_2_count   0.73186    0.07826   9.351  < 2e-16 ***
## category_code_LT01_5_count   0.97084    0.06132  15.833  < 2e-16 ***
## category_code_LT01_6_count   0.41602    0.15254   2.727  0.00661 ** 
## category_code_LT01_9_count   0.37817    0.22519   1.679  0.09372 .  
## category_code_LT01_16_count  0.59851    1.17259   0.510  0.60999    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 0.628813323149982 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9790 -0.7970  0.0652  0.8665  3.4686 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92452    0.09047 109.698  < 2e-16 ***
## category_code_LT01_1_count   0.35601    0.08520   4.178 3.48e-05 ***
## category_code_LT01_2_count   0.62179    0.08946   6.951 1.16e-11 ***
## category_code_LT01_5_count   0.96606    0.06094  15.854  < 2e-16 ***
## category_code_LT01_6_count   0.33786    0.15423   2.191  0.02895 *  
## category_code_LT01_10_count  0.10328    0.11256   0.918  0.35933    
## category_code_LT01_11_count  0.32401    0.11599   2.793  0.00542 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.372 on 491 degrees of freedom
## Multiple R-squared:  0.6333, Adjusted R-squared:  0.6288 
## F-statistic: 141.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 0.622985908154494 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9737 -0.8116  0.0193  0.9515  3.4851 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90808    0.09101 108.870  < 2e-16 ***
## category_code_LT01_1_count   0.42063    0.08365   5.029 6.94e-07 ***
## category_code_LT01_2_count   0.75659    0.07755   9.757  < 2e-16 ***
## category_code_LT01_5_count   0.98214    0.06148  15.975  < 2e-16 ***
## category_code_LT01_6_count   0.40064    0.15465   2.591  0.00986 ** 
## category_code_LT01_10_count  0.11445    0.11342   1.009  0.31343    
## category_code_LT01_12_count -0.06376    0.20858  -0.306  0.75997    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6275, Adjusted R-squared:  0.623 
## F-statistic: 137.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 0.622935767382688 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9729 -0.8122  0.0224  0.9521  3.4843 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90884    0.09102 108.865  < 2e-16 ***
## category_code_LT01_1_count   0.41505    0.08413   4.934 1.11e-06 ***
## category_code_LT01_2_count   0.75214    0.07693   9.777  < 2e-16 ***
## category_code_LT01_5_count   0.97987    0.06126  15.994  < 2e-16 ***
## category_code_LT01_6_count   0.39707    0.15408   2.577   0.0103 *  
## category_code_LT01_10_count  0.11282    0.11347   0.994   0.3206    
## category_code_LT01_13_count  0.04117    0.24541   0.168   0.8668    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6275, Adjusted R-squared:  0.6229 
## F-statistic: 137.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 0.623051674346558 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9747 -0.7990  0.0152  0.9377  3.4802 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91292    0.09157 108.250  < 2e-16 ***
## category_code_LT01_1_count   0.41167    0.08405   4.898 1.32e-06 ***
## category_code_LT01_2_count   0.74887    0.07735   9.682  < 2e-16 ***
## category_code_LT01_5_count   0.97661    0.06182  15.797  < 2e-16 ***
## category_code_LT01_6_count   0.40500    0.15535   2.607  0.00941 ** 
## category_code_LT01_10_count  0.10177    0.11672   0.872  0.38370    
## category_code_LT01_14_count  0.14325    0.33847   0.423  0.67231    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6276, Adjusted R-squared:  0.6231 
## F-statistic: 137.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 0.623134703178391 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9706 -0.8057  0.0266  0.9395  3.4867 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90641    0.09106 108.784  < 2e-16 ***
## category_code_LT01_1_count   0.42584    0.08444   5.043 6.46e-07 ***
## category_code_LT01_2_count   0.75502    0.07677   9.834  < 2e-16 ***
## category_code_LT01_5_count   0.98010    0.06119  16.019  < 2e-16 ***
## category_code_LT01_6_count   0.39786    0.15400   2.584   0.0101 *  
## category_code_LT01_10_count  0.11834    0.11371   1.041   0.2985    
## category_code_LT01_15_count -0.40891    0.76283  -0.536   0.5922    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6277, Adjusted R-squared:  0.6231 
## F-statistic:   138 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 0.623119711926786 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9731 -0.7995  0.0212  0.9592  3.4838 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90939    0.09099 108.901  < 2e-16 ***
## category_code_LT01_1_count   0.41840    0.08298   5.042 6.48e-07 ***
## category_code_LT01_2_count   0.74683    0.07765   9.618  < 2e-16 ***
## category_code_LT01_5_count   0.97936    0.06121  15.999  < 2e-16 ***
## category_code_LT01_6_count   0.40438    0.15476   2.613  0.00925 ** 
## category_code_LT01_10_count  0.11047    0.11351   0.973  0.33095    
## category_code_LT01_16_count  0.60841    1.17568   0.517  0.60504    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6277, Adjusted R-squared:  0.6231 
## F-statistic:   138 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 0.628793748623977 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0042 -0.7874  0.0435  0.8566  3.4466 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94659    0.08727 113.969  < 2e-16 ***
## category_code_LT01_1_count   0.35972    0.08540   4.212 3.01e-05 ***
## category_code_LT01_2_count   0.63016    0.08915   7.069 5.39e-12 ***
## category_code_LT01_5_count   0.97060    0.06113  15.877  < 2e-16 ***
## category_code_LT01_6_count   0.36911    0.15271   2.417   0.0160 *  
## category_code_LT01_11_count  0.35030    0.11865   2.952   0.0033 ** 
## category_code_LT01_12_count -0.19127    0.21175  -0.903   0.3668    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.372 on 491 degrees of freedom
## Multiple R-squared:  0.6333, Adjusted R-squared:  0.6288 
## F-statistic: 141.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 0.62818457207903 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0009 -0.7939  0.0580  0.8745  3.4467 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94647    0.08735 113.871  < 2e-16 ***
## category_code_LT01_1_count   0.35302    0.08623   4.094 4.96e-05 ***
## category_code_LT01_2_count   0.62836    0.08931   7.036 6.69e-12 ***
## category_code_LT01_5_count   0.96592    0.06104  15.824  < 2e-16 ***
## category_code_LT01_6_count   0.36027    0.15255   2.362  0.01859 *  
## category_code_LT01_11_count  0.32704    0.11611   2.817  0.00505 ** 
## category_code_LT01_13_count  0.02450    0.24370   0.101  0.91997    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 491 degrees of freedom
## Multiple R-squared:  0.6327, Adjusted R-squared:  0.6282 
## F-statistic: 140.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 0.628417682105748 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0001 -0.7940  0.0520  0.8751  3.4444 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94876    0.08742 113.807  < 2e-16 ***
## category_code_LT01_1_count   0.34752    0.08608   4.037 6.27e-05 ***
## category_code_LT01_2_count   0.62298    0.08977   6.939 1.25e-11 ***
## category_code_LT01_5_count   0.96144    0.06155  15.621  < 2e-16 ***
## category_code_LT01_6_count   0.36807    0.15314   2.403  0.01661 *  
## category_code_LT01_11_count  0.32539    0.11605   2.804  0.00525 ** 
## category_code_LT01_14_count  0.18419    0.32656   0.564  0.57299    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 491 degrees of freedom
## Multiple R-squared:  0.6329, Adjusted R-squared:  0.6284 
## F-statistic: 141.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 0.628369355868758 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9998 -0.7926  0.0584  0.8669  3.4478 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94540    0.08735 113.862  < 2e-16 ***
## category_code_LT01_1_count   0.36197    0.08658   4.181 3.44e-05 ***
## category_code_LT01_2_count   0.63056    0.08925   7.065 5.53e-12 ***
## category_code_LT01_5_count   0.96594    0.06097  15.842  < 2e-16 ***
## category_code_LT01_6_count   0.36206    0.15252   2.374  0.01799 *  
## category_code_LT01_11_count  0.32843    0.11601   2.831  0.00483 ** 
## category_code_LT01_15_count -0.38082    0.75524  -0.504  0.61433    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 491 degrees of freedom
## Multiple R-squared:  0.6329, Adjusted R-squared:  0.6284 
## F-statistic: 141.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 0.628413087839055 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0005 -0.7945  0.0562  0.8794  3.4465 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94661    0.08732 113.910  < 2e-16 ***
## category_code_LT01_1_count   0.35550    0.08526   4.170 3.61e-05 ***
## category_code_LT01_2_count   0.62194    0.09002   6.909 1.52e-11 ***
## category_code_LT01_5_count   0.96514    0.06100  15.823  < 2e-16 ***
## category_code_LT01_6_count   0.36780    0.15311   2.402  0.01667 *  
## category_code_LT01_11_count  0.32715    0.11599   2.820  0.00499 ** 
## category_code_LT01_16_count  0.65126    1.16583   0.559  0.57667    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 491 degrees of freedom
## Multiple R-squared:  0.6329, Adjusted R-squared:  0.6284 
## F-statistic: 141.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 0.622237146927411 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9977 -0.8140  0.0402  0.9390  3.4608 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93237    0.08791 112.985  < 2e-16 ***
## category_code_LT01_1_count   0.41634    0.08484   4.908 1.26e-06 ***
## category_code_LT01_2_count   0.76436    0.07734   9.883  < 2e-16 ***
## category_code_LT01_5_count   0.98172    0.06160  15.936  < 2e-16 ***
## category_code_LT01_6_count   0.42608    0.15290   2.787  0.00553 ** 
## category_code_LT01_12_count -0.05860    0.20872  -0.281  0.77902    
## category_code_LT01_13_count  0.05093    0.24548   0.207  0.83572    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6268, Adjusted R-squared:  0.6222 
## F-statistic: 137.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 0.62254962697988 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9970 -0.8186  0.0401  0.9565  3.4581 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93509    0.08797 112.932  < 2e-16 ***
## category_code_LT01_1_count   0.41107    0.08456   4.862 1.57e-06 ***
## category_code_LT01_2_count   0.75815    0.07787   9.736  < 2e-16 ***
## category_code_LT01_5_count   0.97677    0.06207  15.738  < 2e-16 ***
## category_code_LT01_6_count   0.43545    0.15354   2.836  0.00476 ** 
## category_code_LT01_12_count -0.06812    0.20916  -0.326  0.74479    
## category_code_LT01_14_count  0.22113    0.32980   0.670  0.50286    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6271, Adjusted R-squared:  0.6225 
## F-statistic: 137.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 0.6223725902739 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9969 -0.7987  0.0376  0.9474  3.4620 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93120    0.08791 112.965  < 2e-16 ***
## category_code_LT01_1_count   0.42676    0.08525   5.006 7.76e-07 ***
## category_code_LT01_2_count   0.76787    0.07724   9.941  < 2e-16 ***
## category_code_LT01_5_count   0.98223    0.06153  15.963  < 2e-16 ***
## category_code_LT01_6_count   0.42790    0.15293   2.798  0.00534 ** 
## category_code_LT01_12_count -0.06267    0.20890  -0.300  0.76432    
## category_code_LT01_15_count -0.35675    0.76203  -0.468  0.63988    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6269, Adjusted R-squared:  0.6224 
## F-statistic: 137.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 0.622451158061254 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9974 -0.8007  0.0454  0.9537  3.4607 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93242    0.08788 113.022  < 2e-16 ***
## category_code_LT01_1_count   0.42031    0.08372   5.021 7.22e-07 ***
## category_code_LT01_2_count   0.75842    0.07812   9.709  < 2e-16 ***
## category_code_LT01_5_count   0.98120    0.06155  15.940  < 2e-16 ***
## category_code_LT01_6_count   0.43336    0.15347   2.824  0.00494 ** 
## category_code_LT01_12_count -0.05750    0.20866  -0.276  0.78299    
## category_code_LT01_16_count  0.66621    1.17515   0.567  0.57103    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.627,  Adjusted R-squared:  0.6225 
## F-statistic: 137.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 0.622503425684216 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9958 -0.8120  0.0444  0.9500  3.4577 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93547    0.08798 112.925  < 2e-16 ***
## category_code_LT01_1_count   0.40489    0.08517   4.754 2.62e-06 ***
## category_code_LT01_2_count   0.75328    0.07738   9.735  < 2e-16 ***
## category_code_LT01_5_count   0.97440    0.06191  15.739  < 2e-16 ***
## category_code_LT01_6_count   0.43109    0.15277   2.822  0.00497 ** 
## category_code_LT01_13_count  0.05262    0.24541   0.214  0.83032    
## category_code_LT01_14_count  0.21455    0.32902   0.652  0.51465    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6271, Adjusted R-squared:  0.6225 
## F-statistic: 137.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 0.62232418729394 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9958 -0.8025  0.0441  0.9311  3.4615 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93166    0.08792 112.961  < 2e-16 ***
## category_code_LT01_1_count   0.42084    0.08587   4.901  1.3e-06 ***
## category_code_LT01_2_count   0.76324    0.07661   9.962  < 2e-16 ***
## category_code_LT01_5_count   0.98000    0.06131  15.983  < 2e-16 ***
## category_code_LT01_6_count   0.42389    0.15223   2.785  0.00557 ** 
## category_code_LT01_13_count  0.04053    0.24642   0.164  0.86942    
## category_code_LT01_15_count -0.33491    0.76432  -0.438  0.66145    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6269, Adjusted R-squared:  0.6223 
## F-statistic: 137.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 0.622432375789058 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9963 -0.8032  0.0468  0.9440  3.4603 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93286    0.08788 113.024  < 2e-16 ***
## category_code_LT01_1_count   0.41426    0.08418   4.921 1.18e-06 ***
## category_code_LT01_2_count   0.75369    0.07752   9.722  < 2e-16 ***
## category_code_LT01_5_count   0.97890    0.06134  15.959  < 2e-16 ***
## category_code_LT01_6_count   0.43023    0.15282   2.815  0.00507 ** 
## category_code_LT01_13_count  0.05574    0.24559   0.227  0.82054    
## category_code_LT01_16_count  0.67840    1.17607   0.577  0.56431    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.627,  Adjusted R-squared:  0.6224 
## F-statistic: 137.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 0.622625216872946 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9949 -0.8172  0.0406  0.9456  3.4588 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93432    0.08799 112.905  < 2e-16 ***
## category_code_LT01_1_count   0.41501    0.08544   4.857  1.6e-06 ***
## category_code_LT01_2_count   0.75659    0.07723   9.796  < 2e-16 ***
## category_code_LT01_5_count   0.97487    0.06183  15.766  < 2e-16 ***
## category_code_LT01_6_count   0.43244    0.15278   2.831  0.00484 ** 
## category_code_LT01_14_count  0.21285    0.32893   0.647  0.51787    
## category_code_LT01_15_count -0.34408    0.76096  -0.452  0.65135    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6272, Adjusted R-squared:  0.6226 
## F-statistic: 137.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 0.62275493549188 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9954 -0.8096  0.0505  0.9612  3.4575 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93568    0.08795 112.969  < 2e-16 ***
## category_code_LT01_1_count   0.40864    0.08398   4.866 1.54e-06 ***
## category_code_LT01_2_count   0.74645    0.07825   9.539  < 2e-16 ***
## category_code_LT01_5_count   0.97354    0.06187  15.735  < 2e-16 ***
## category_code_LT01_6_count   0.43956    0.15343   2.865  0.00435 ** 
## category_code_LT01_14_count  0.22625    0.32954   0.687  0.49268    
## category_code_LT01_16_count  0.71920    1.17703   0.611  0.54147    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6273, Adjusted R-squared:  0.6228 
## F-statistic: 137.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 0.622540744744698 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9955 -0.8012  0.0445  0.9493  3.4614 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93174    0.08789 113.002  < 2e-16 ***
## category_code_LT01_1_count   0.42424    0.08449   5.021  7.2e-07 ***
## category_code_LT01_2_count   0.75724    0.07737   9.788  < 2e-16 ***
## category_code_LT01_5_count   0.97941    0.06126  15.987  < 2e-16 ***
## category_code_LT01_6_count   0.43124    0.15281   2.822  0.00496 ** 
## category_code_LT01_15_count -0.33404    0.76135  -0.439  0.66104    
## category_code_LT01_16_count  0.65317    1.17547   0.556  0.57869    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6271, Adjusted R-squared:  0.6225 
## F-statistic: 137.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 0.627733676670726 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0119 -0.7936  0.0637  0.9106  3.4468 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94637    0.08722 114.034  < 2e-16 ***
## category_code_LT01_1_count  0.39311    0.08301   4.735 2.86e-06 ***
## category_code_LT01_2_count  0.74303    0.07446   9.979  < 2e-16 ***
## category_code_LT01_5_count  0.98195    0.06140  15.993  < 2e-16 ***
## category_code_LT01_7_count  0.51411    0.15177   3.387 0.000762 ***
## category_code_LT01_8_count -0.17361    0.27237  -0.637 0.524160    
## category_code_LT01_9_count  0.34045    0.22506   1.513 0.131001    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6322, Adjusted R-squared:  0.6277 
## F-statistic: 140.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 0.626995221520172 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9914 -0.7689  0.0492  0.9069  3.4715 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92168    0.09059 109.523  < 2e-16 ***
## category_code_LT01_1_count   0.40075    0.08297   4.830 1.83e-06 ***
## category_code_LT01_2_count   0.74979    0.07426  10.097  < 2e-16 ***
## category_code_LT01_5_count   0.98808    0.06128  16.123  < 2e-16 ***
## category_code_LT01_7_count   0.52143    0.15177   3.436 0.000642 ***
## category_code_LT01_8_count  -0.16782    0.27257  -0.616 0.538388    
## category_code_LT01_10_count  0.12801    0.11177   1.145 0.252653    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6315, Adjusted R-squared:  0.627 
## F-statistic: 140.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 0.630142775974733 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0211 -0.7471  0.0278  0.8560  3.4341 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95902    0.08701 114.455  < 2e-16 ***
## category_code_LT01_1_count   0.35212    0.08511   4.137 4.14e-05 ***
## category_code_LT01_2_count   0.65421    0.08658   7.556 2.05e-13 ***
## category_code_LT01_5_count   0.97701    0.06124  15.955  < 2e-16 ***
## category_code_LT01_7_count   0.44195    0.15588   2.835  0.00477 ** 
## category_code_LT01_8_count  -0.14138    0.27148  -0.521  0.60275    
## category_code_LT01_11_count  0.27824    0.11863   2.345  0.01940 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6346, Adjusted R-squared:  0.6301 
## F-statistic: 142.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 0.625999325062828 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0199 -0.7723  0.0276  0.9174  3.4437 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.949460   0.087404 113.833  < 2e-16 ***
## category_code_LT01_1_count   0.399760   0.083884   4.766 2.48e-06 ***
## category_code_LT01_2_count   0.763051   0.074832  10.197  < 2e-16 ***
## category_code_LT01_5_count   0.989010   0.061691  16.032  < 2e-16 ***
## category_code_LT01_7_count   0.536849   0.151382   3.546 0.000428 ***
## category_code_LT01_8_count  -0.161068   0.273037  -0.590 0.555519    
## category_code_LT01_12_count  0.005545   0.206824   0.027 0.978620    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 0.626062482328558 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0203 -0.7760  0.0264  0.9121  3.4439 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94924    0.08740 113.839  < 2e-16 ***
## category_code_LT01_1_count   0.40361    0.08397   4.807 2.04e-06 ***
## category_code_LT01_2_count   0.76425    0.07344  10.406  < 2e-16 ***
## category_code_LT01_5_count   0.98992    0.06140  16.121  < 2e-16 ***
## category_code_LT01_7_count   0.54179    0.15234   3.557 0.000412 ***
## category_code_LT01_8_count  -0.16603    0.27344  -0.607 0.544002    
## category_code_LT01_13_count -0.07120    0.24619  -0.289 0.772535    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6306, Adjusted R-squared:  0.6261 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 0.626013415857638 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0199 -0.7710  0.0300  0.9087  3.4431 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95009    0.08753 113.682  < 2e-16 ***
## category_code_LT01_1_count   0.39860    0.08375   4.759 2.56e-06 ***
## category_code_LT01_2_count   0.76242    0.07376  10.337  < 2e-16 ***
## category_code_LT01_5_count   0.98818    0.06178  15.995  < 2e-16 ***
## category_code_LT01_7_count   0.53527    0.15179   3.526 0.000461 ***
## category_code_LT01_8_count  -0.16121    0.27288  -0.591 0.554951    
## category_code_LT01_14_count  0.04533    0.32699   0.139 0.889799    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 0.626030524478665 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0196 -0.7631  0.0279  0.9128  3.4441 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94904    0.08742 113.805  < 2e-16 ***
## category_code_LT01_1_count   0.40346    0.08471   4.763 2.52e-06 ***
## category_code_LT01_2_count   0.76473    0.07366  10.382  < 2e-16 ***
## category_code_LT01_5_count   0.98920    0.06135  16.123  < 2e-16 ***
## category_code_LT01_7_count   0.53542    0.15153   3.533 0.000449 ***
## category_code_LT01_8_count  -0.16037    0.27287  -0.588 0.556979    
## category_code_LT01_15_count -0.15474    0.75794  -0.204 0.838312    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 0.626118255971327 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0202 -0.7709  0.0272  0.9204  3.4433 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94982    0.08739 113.851  < 2e-16 ***
## category_code_LT01_1_count   0.40126    0.08312   4.828 1.85e-06 ***
## category_code_LT01_2_count   0.75944    0.07408  10.252  < 2e-16 ***
## category_code_LT01_5_count   0.98892    0.06135  16.119  < 2e-16 ***
## category_code_LT01_7_count   0.53788    0.15138   3.553 0.000417 ***
## category_code_LT01_8_count  -0.16647    0.27320  -0.609 0.542587    
## category_code_LT01_16_count  0.46188    1.16604   0.396 0.692194    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6306, Adjusted R-squared:  0.6261 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 0.628136188183716 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9824 -0.7862  0.0826  0.9410  3.4718 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92138    0.09043 109.711  < 2e-16 ***
## category_code_LT01_1_count   0.39246    0.08293   4.732 2.91e-06 ***
## category_code_LT01_2_count   0.73379    0.07513   9.767  < 2e-16 ***
## category_code_LT01_5_count   0.97544    0.06066  16.080  < 2e-16 ***
## category_code_LT01_7_count   0.49983    0.15209   3.286  0.00109 ** 
## category_code_LT01_9_count   0.31087    0.22632   1.374  0.17020    
## category_code_LT01_10_count  0.10879    0.11231   0.969  0.33322    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 491 degrees of freedom
## Multiple R-squared:  0.6326, Adjusted R-squared:  0.6281 
## F-statistic: 140.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 0.631438573725333 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0084 -0.7620  0.0343  0.8641  3.4386 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95457    0.08686 114.610  < 2e-16 ***
## category_code_LT01_1_count   0.34482    0.08498   4.058 5.77e-05 ***
## category_code_LT01_2_count   0.63745    0.08721   7.309 1.10e-12 ***
## category_code_LT01_5_count   0.96513    0.06057  15.934  < 2e-16 ***
## category_code_LT01_7_count   0.41959    0.15608   2.688  0.00743 ** 
## category_code_LT01_9_count   0.31664    0.22399   1.414  0.15810    
## category_code_LT01_11_count  0.27387    0.11845   2.312  0.02118 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6359, Adjusted R-squared:  0.6314 
## F-statistic: 142.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 0.627425657007581 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0062 -0.7901  0.0646  0.9158  3.4484 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.9447921  0.0872252 114.013  < 2e-16 ***
## category_code_LT01_1_count  0.3913699  0.0838204   4.669 3.91e-06 ***
## category_code_LT01_2_count  0.7438076  0.0758764   9.803  < 2e-16 ***
## category_code_LT01_5_count  0.9759858  0.0610874  15.977  < 2e-16 ***
## category_code_LT01_7_count  0.5113284  0.1517744   3.369 0.000814 ***
## category_code_LT01_9_count  0.3359930  0.2250463   1.493 0.136081    
## category_code_LT01_12_count 0.0008947  0.2063026   0.004 0.996541    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6319, Adjusted R-squared:  0.6274 
## F-statistic: 140.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 0.627438617321568 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0063 -0.7897  0.0626  0.9146  3.4485 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94470    0.08723 114.011  < 2e-16 ***
## category_code_LT01_1_count   0.39304    0.08393   4.683 3.66e-06 ***
## category_code_LT01_2_count   0.74438    0.07458   9.981  < 2e-16 ***
## category_code_LT01_5_count   0.97632    0.06076  16.068  < 2e-16 ***
## category_code_LT01_7_count   0.51368    0.15284   3.361 0.000837 ***
## category_code_LT01_9_count   0.33363    0.22577   1.478 0.140123    
## category_code_LT01_13_count -0.03217    0.24600  -0.131 0.896015    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6319, Adjusted R-squared:  0.6274 
## F-statistic: 140.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 0.62742737761026 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0062 -0.7936  0.0652  0.9163  3.4481 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94502    0.08735 113.847  < 2e-16 ***
## category_code_LT01_1_count   0.39092    0.08365   4.673 3.84e-06 ***
## category_code_LT01_2_count   0.74356    0.07476   9.945  < 2e-16 ***
## category_code_LT01_5_count   0.97568    0.06112  15.963  < 2e-16 ***
## category_code_LT01_7_count   0.51083    0.15213   3.358 0.000846 ***
## category_code_LT01_9_count   0.33538    0.22541   1.488 0.137429    
## category_code_LT01_14_count  0.01563    0.32688   0.048 0.961883    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6319, Adjusted R-squared:  0.6274 
## F-statistic: 140.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 0.627447148999044 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0059 -0.7929  0.0673  0.9135  3.4487 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94447    0.08724 113.986  < 2e-16 ***
## category_code_LT01_1_count   0.39423    0.08467   4.656 4.15e-06 ***
## category_code_LT01_2_count   0.74499    0.07477   9.964  < 2e-16 ***
## category_code_LT01_5_count   0.97606    0.06071  16.076  < 2e-16 ***
## category_code_LT01_7_count   0.51024    0.15191   3.359 0.000843 ***
## category_code_LT01_9_count   0.33496    0.22512   1.488 0.137426    
## category_code_LT01_15_count -0.12741    0.75677  -0.168 0.866372    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6319, Adjusted R-squared:  0.6274 
## F-statistic: 140.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 0.627502095952998 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0062 -0.7848  0.0690  0.9188  3.4481 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94507    0.08722 114.023  < 2e-16 ***
## category_code_LT01_1_count   0.39237    0.08305   4.724 3.02e-06 ***
## category_code_LT01_2_count   0.74082    0.07508   9.867  < 2e-16 ***
## category_code_LT01_5_count   0.97570    0.06072  16.069  < 2e-16 ***
## category_code_LT01_7_count   0.51224    0.15178   3.375 0.000797 ***
## category_code_LT01_9_count   0.33369    0.22514   1.482 0.138944    
## category_code_LT01_16_count  0.36916    1.16290   0.317 0.751036    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.632,  Adjusted R-squared:  0.6275 
## F-statistic: 140.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 0.630783566151106 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9899 -0.7279  0.0509  0.8474  3.4612 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93198    0.09024 110.059  < 2e-16 ***
## category_code_LT01_1_count   0.35162    0.08498   4.138 4.12e-05 ***
## category_code_LT01_2_count   0.64300    0.08711   7.381 6.76e-13 ***
## category_code_LT01_5_count   0.97094    0.06044  16.065  < 2e-16 ***
## category_code_LT01_7_count   0.42591    0.15610   2.728  0.00659 ** 
## category_code_LT01_10_count  0.11792    0.11124   1.060  0.28962    
## category_code_LT01_11_count  0.27598    0.11853   2.328  0.02030 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6352, Adjusted R-squared:  0.6308 
## F-statistic: 142.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 0.626708585699552 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9863 -0.7739  0.0607  0.9182  3.4728 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.920391   0.090615 109.479  < 2e-16 ***
## category_code_LT01_1_count   0.399517   0.083777   4.769 2.45e-06 ***
## category_code_LT01_2_count   0.751093   0.075596   9.936  < 2e-16 ***
## category_code_LT01_5_count   0.982542   0.060942  16.123  < 2e-16 ***
## category_code_LT01_7_count   0.518580   0.151770   3.417 0.000686 ***
## category_code_LT01_10_count  0.126666   0.111890   1.132 0.258160    
## category_code_LT01_12_count -0.008665   0.206687  -0.042 0.966577    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6312, Adjusted R-squared:  0.6267 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 0.626765199230473 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9862 -0.7741  0.0555  0.9201  3.4731 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92006    0.09061 109.484  < 2e-16 ***
## category_code_LT01_1_count   0.40235    0.08382   4.800 2.11e-06 ***
## category_code_LT01_2_count   0.75121    0.07432  10.108  < 2e-16 ***
## category_code_LT01_5_count   0.98279    0.06060  16.218  < 2e-16 ***
## category_code_LT01_7_count   0.52318    0.15264   3.427 0.000661 ***
## category_code_LT01_10_count  0.12718    0.11181   1.137 0.255899    
## category_code_LT01_13_count -0.06778    0.24549  -0.276 0.782583    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 0.62671677929086 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9856 -0.7753  0.0576  0.9191  3.4738 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91932    0.09116 108.812  < 2e-16 ***
## category_code_LT01_1_count   0.40026    0.08368   4.783 2.29e-06 ***
## category_code_LT01_2_count   0.75105    0.07444  10.089  < 2e-16 ***
## category_code_LT01_5_count   0.98307    0.06100  16.115  < 2e-16 ***
## category_code_LT01_7_count   0.51959    0.15200   3.418 0.000683 ***
## category_code_LT01_10_count  0.12921    0.11444   1.129 0.259413    
## category_code_LT01_14_count -0.03744    0.33440  -0.112 0.910901    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6312, Adjusted R-squared:  0.6267 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 0.626779961907043 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9849 -0.7727  0.0555  0.9187  3.4740 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91918    0.09069 109.377  < 2e-16 ***
## category_code_LT01_1_count   0.40419    0.08461   4.777 2.35e-06 ***
## category_code_LT01_2_count   0.75213    0.07446  10.101  < 2e-16 ***
## category_code_LT01_5_count   0.98228    0.06057  16.218  < 2e-16 ***
## category_code_LT01_7_count   0.51613    0.15197   3.396 0.000738 ***
## category_code_LT01_10_count  0.12951    0.11221   1.154 0.248998    
## category_code_LT01_15_count -0.23508    0.76008  -0.309 0.757234    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 0.626786427981819 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9865 -0.7732  0.0627  0.9232  3.4721 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92101    0.09061 109.492  < 2e-16 ***
## category_code_LT01_1_count   0.39994    0.08299   4.819 1.93e-06 ***
## category_code_LT01_2_count   0.74741    0.07489   9.980  < 2e-16 ***
## category_code_LT01_5_count   0.98190    0.06058  16.209  < 2e-16 ***
## category_code_LT01_7_count   0.51957    0.15178   3.423 0.000671 ***
## category_code_LT01_10_count  0.12511    0.11186   1.118 0.263909    
## category_code_LT01_16_count  0.37576    1.16423   0.323 0.747022    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 0.630173681330082 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0189 -0.7476  0.0237  0.8549  3.4351 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95807    0.08698 114.490  < 2e-16 ***
## category_code_LT01_1_count   0.35430    0.08533   4.152 3.88e-05 ***
## category_code_LT01_2_count   0.65602    0.08665   7.571 1.85e-13 ***
## category_code_LT01_5_count   0.97521    0.06075  16.053  < 2e-16 ***
## category_code_LT01_7_count   0.43303    0.15610   2.774  0.00575 ** 
## category_code_LT01_11_count  0.29597    0.12191   2.428  0.01555 *  
## category_code_LT01_12_count -0.11810    0.21134  -0.559  0.57655    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6346, Adjusted R-squared:  0.6302 
## F-statistic: 142.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 0.629990918049703 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0165 -0.7471  0.0340  0.8550  3.4356 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95754    0.08700 114.453  < 2e-16 ***
## category_code_LT01_1_count   0.35347    0.08588   4.116 4.52e-05 ***
## category_code_LT01_2_count   0.65461    0.08663   7.556 2.05e-13 ***
## category_code_LT01_5_count   0.97251    0.06052  16.068  < 2e-16 ***
## category_code_LT01_7_count   0.44315    0.15666   2.829  0.00487 ** 
## category_code_LT01_11_count  0.28029    0.11860   2.363  0.01850 *  
## category_code_LT01_13_count -0.06446    0.24437  -0.264  0.79205    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:   0.63 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 0.629952214263953 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0163 -0.7480  0.0347  0.8609  3.4348 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95839    0.08712 114.300  < 2e-16 ***
## category_code_LT01_1_count   0.34892    0.08572   4.070 5.47e-05 ***
## category_code_LT01_2_count   0.65294    0.08691   7.513 2.76e-13 ***
## category_code_LT01_5_count   0.97103    0.06093  15.936  < 2e-16 ***
## category_code_LT01_7_count   0.43728    0.15621   2.799  0.00532 ** 
## category_code_LT01_11_count  0.28014    0.11860   2.362  0.01857 *  
## category_code_LT01_14_count  0.04391    0.32525   0.135  0.89267    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6344, Adjusted R-squared:   0.63 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 0.630001463989091 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0159 -0.7423  0.0348  0.8591  3.4359 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95724    0.08702 114.431  < 2e-16 ***
## category_code_LT01_1_count   0.35493    0.08652   4.102 4.79e-05 ***
## category_code_LT01_2_count   0.65530    0.08672   7.556 2.05e-13 ***
## category_code_LT01_5_count   0.97201    0.06049  16.068  < 2e-16 ***
## category_code_LT01_7_count   0.43643    0.15601   2.798  0.00535 ** 
## category_code_LT01_11_count  0.28127    0.11866   2.370  0.01816 *  
## category_code_LT01_15_count -0.21808    0.75431  -0.289  0.77262    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:   0.63 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 0.630045586513917 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0164 -0.7476  0.0356  0.8613  3.4351 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95807    0.08699 114.468  < 2e-16 ***
## category_code_LT01_1_count   0.35139    0.08510   4.129 4.28e-05 ***
## category_code_LT01_2_count   0.65009    0.08719   7.456 4.06e-13 ***
## category_code_LT01_5_count   0.97157    0.06050  16.059  < 2e-16 ***
## category_code_LT01_7_count   0.43963    0.15580   2.822  0.00497 ** 
## category_code_LT01_11_count  0.28032    0.11859   2.364  0.01848 *  
## category_code_LT01_16_count  0.43673    1.15833   0.377  0.70631    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:   0.63 
## F-statistic: 142.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 0.625781751210846 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0147 -0.7845  0.0381  0.9101  3.4454 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.947734   0.087396 113.824  < 2e-16 ***
## category_code_LT01_1_count   0.401328   0.084717   4.737 2.84e-06 ***
## category_code_LT01_2_count   0.764555   0.074889  10.209  < 2e-16 ***
## category_code_LT01_5_count   0.984020   0.061040  16.121  < 2e-16 ***
## category_code_LT01_7_count   0.538167   0.152278   3.534 0.000448 ***
## category_code_LT01_12_count  0.001744   0.206766   0.008 0.993272    
## category_code_LT01_13_count -0.061354   0.245759  -0.250 0.802962    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6258 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 0.625747590392587 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.7754  0.0448  0.8992  3.4446 
## 
## Coefficients:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.9485635  0.0875186 113.674  < 2e-16 ***
## category_code_LT01_1_count   0.3970353  0.0844661   4.701 3.38e-06 ***
## category_code_LT01_2_count   0.7630294  0.0751203  10.157  < 2e-16 ***
## category_code_LT01_5_count   0.9826366  0.0614047  16.003  < 2e-16 ***
## category_code_LT01_7_count   0.5324732  0.1517773   3.508 0.000493 ***
## category_code_LT01_12_count -0.0004348  0.2071683  -0.002 0.998326    
## category_code_LT01_14_count  0.0433565  0.3277234   0.132 0.894804    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6257 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 0.625767430327759 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0142 -0.7679  0.0387  0.9103  3.4456 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.947532   0.087416 113.795  < 2e-16 ***
## category_code_LT01_1_count   0.401926   0.085608   4.695 3.46e-06 ***
## category_code_LT01_2_count   0.765329   0.075162  10.182  < 2e-16 ***
## category_code_LT01_5_count   0.983644   0.061014  16.122  < 2e-16 ***
## category_code_LT01_7_count   0.532529   0.151508   3.515 0.000481 ***
## category_code_LT01_12_count -0.000601   0.206956  -0.003 0.997684    
## category_code_LT01_15_count -0.158342   0.758900  -0.209 0.834810    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6258 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 0.625835633516252 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.7757  0.0441  0.9231  3.4449 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.948245   0.087389 113.838  < 2e-16 ***
## category_code_LT01_1_count  0.399334   0.083911   4.759 2.56e-06 ***
## category_code_LT01_2_count  0.760139   0.075535  10.063  < 2e-16 ***
## category_code_LT01_5_count  0.983094   0.061019  16.111  < 2e-16 ***
## category_code_LT01_7_count  0.534848   0.151356   3.534 0.000449 ***
## category_code_LT01_12_count 0.002354   0.206764   0.011 0.990921    
## category_code_LT01_16_count 0.424936   1.165010   0.365 0.715456    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6304, Adjusted R-squared:  0.6258 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 0.625794011038461 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0147 -0.7821  0.0416  0.9035  3.4448 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94832    0.08752 113.671  < 2e-16 ***
## category_code_LT01_1_count   0.40004    0.08463   4.727 2.98e-06 ***
## category_code_LT01_2_count   0.76374    0.07384  10.344  < 2e-16 ***
## category_code_LT01_5_count   0.98314    0.06111  16.087  < 2e-16 ***
## category_code_LT01_7_count   0.53668    0.15272   3.514 0.000482 ***
## category_code_LT01_13_count -0.06067    0.24580  -0.247 0.805161    
## category_code_LT01_14_count  0.04158    0.32714   0.127 0.898904    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6258 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 0.625822344713586 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0143 -0.7702  0.0366  0.9043  3.4459 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94725    0.08741 113.794  < 2e-16 ***
## category_code_LT01_1_count   0.40551    0.08576   4.728 2.96e-06 ***
## category_code_LT01_2_count   0.76619    0.07375  10.389  < 2e-16 ***
## category_code_LT01_5_count   0.98415    0.06067  16.223  < 2e-16 ***
## category_code_LT01_7_count   0.53690    0.15237   3.524 0.000465 ***
## category_code_LT01_13_count -0.06621    0.24664  -0.268 0.788462    
## category_code_LT01_15_count -0.17574    0.76092  -0.231 0.817449    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6258 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 0.625878281420877 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0147 -0.7813  0.0427  0.9158  3.4451 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94803    0.08739 113.838  < 2e-16 ***
## category_code_LT01_1_count   0.40229    0.08395   4.792 2.19e-06 ***
## category_code_LT01_2_count   0.76106    0.07415  10.263  < 2e-16 ***
## category_code_LT01_5_count   0.98364    0.06067  16.212  < 2e-16 ***
## category_code_LT01_7_count   0.53880    0.15227   3.539 0.000441 ***
## category_code_LT01_13_count -0.05824    0.24587  -0.237 0.812867    
## category_code_LT01_16_count  0.41497    1.16555   0.356 0.721970    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6304, Adjusted R-squared:  0.6259 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 0.625780634158229 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0142 -0.7664  0.0462  0.8958  3.4450 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94815    0.08754 113.644  < 2e-16 ***
## category_code_LT01_1_count   0.40048    0.08538   4.691 3.53e-06 ***
## category_code_LT01_2_count   0.76432    0.07405  10.322  < 2e-16 ***
## category_code_LT01_5_count   0.98266    0.06108  16.089  < 2e-16 ***
## category_code_LT01_7_count   0.53105    0.15192   3.496 0.000516 ***
## category_code_LT01_14_count  0.04306    0.32708   0.132 0.895312    
## category_code_LT01_15_count -0.15788    0.75818  -0.208 0.835135    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6258 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 0.625853163188985 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0145 -0.7713  0.0502  0.9008  3.4442 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94896    0.08751 113.686  < 2e-16 ***
## category_code_LT01_1_count   0.39787    0.08376   4.750 2.67e-06 ***
## category_code_LT01_2_count   0.75911    0.07451  10.189  < 2e-16 ***
## category_code_LT01_5_count   0.98205    0.06109  16.075  < 2e-16 ***
## category_code_LT01_7_count   0.53314    0.15176   3.513 0.000484 ***
## category_code_LT01_14_count  0.04981    0.32751   0.152 0.879171    
## category_code_LT01_16_count  0.43421    1.16652   0.372 0.709888    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6304, Adjusted R-squared:  0.6259 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 0.625865141698079 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0142 -0.7654  0.0434  0.9149  3.4453 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94784    0.08741 113.810  < 2e-16 ***
## category_code_LT01_1_count   0.40272    0.08472   4.753 2.63e-06 ***
## category_code_LT01_2_count   0.76161    0.07438  10.239  < 2e-16 ***
## category_code_LT01_5_count   0.98321    0.06064  16.214  < 2e-16 ***
## category_code_LT01_7_count   0.53347    0.15151   3.521  0.00047 ***
## category_code_LT01_15_count -0.14951    0.75848  -0.197  0.84382    
## category_code_LT01_16_count  0.41736    1.16545   0.358  0.72042    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6304, Adjusted R-squared:  0.6259 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 0.620199715703549 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9893 -0.7725  0.0266  0.9206  3.4810 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91212    0.09136 108.499  < 2e-16 ***
## category_code_LT01_1_count   0.43881    0.08274   5.303 1.72e-07 ***
## category_code_LT01_2_count   0.80202    0.07293  10.997  < 2e-16 ***
## category_code_LT01_5_count   0.99883    0.06179  16.164  < 2e-16 ***
## category_code_LT01_8_count  -0.15419    0.27506  -0.561   0.5753    
## category_code_LT01_9_count   0.38182    0.22791   1.675   0.0945 .  
## category_code_LT01_10_count  0.13894    0.11319   1.228   0.2202    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6248, Adjusted R-squared:  0.6202 
## F-statistic: 136.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 0.626180185628742 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0200 -0.7762  0.0687  0.8472  3.4379 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95528    0.08750 113.769  < 2e-16 ***
## category_code_LT01_1_count   0.36776    0.08529   4.312 1.96e-05 ***
## category_code_LT01_2_count   0.66266    0.08733   7.588 1.64e-13 ***
## category_code_LT01_5_count   0.98079    0.06161  15.918  < 2e-16 ***
## category_code_LT01_8_count  -0.12752    0.27290  -0.467  0.64051    
## category_code_LT01_9_count   0.37280    0.22486   1.658  0.09798 .  
## category_code_LT01_11_count  0.35355    0.11540   3.064  0.00231 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6307, Adjusted R-squared:  0.6262 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 0.619034136109423 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0197 -0.7911  0.0119  0.9017  3.4513 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.941843   0.088228 112.684  < 2e-16 ***
## category_code_LT01_1_count   0.438616   0.083678   5.242 2.37e-07 ***
## category_code_LT01_2_count   0.816913   0.073474  11.118  < 2e-16 ***
## category_code_LT01_5_count   0.999809   0.062218  16.070  < 2e-16 ***
## category_code_LT01_8_count  -0.147104   0.275584  -0.534    0.594    
## category_code_LT01_9_count   0.415875   0.226559   1.836    0.067 .  
## category_code_LT01_12_count  0.001664   0.208738   0.008    0.994    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6236, Adjusted R-squared:  0.619 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 0.619076309961159 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0194 -0.7913  0.0142  0.8989  3.4512 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94200    0.08822 112.691  < 2e-16 ***
## category_code_LT01_1_count   0.43537    0.08409   5.178 3.28e-07 ***
## category_code_LT01_2_count   0.81551    0.07230  11.280  < 2e-16 ***
## category_code_LT01_5_count   0.99902    0.06198  16.117  < 2e-16 ***
## category_code_LT01_8_count  -0.14317    0.27590  -0.519   0.6040    
## category_code_LT01_9_count   0.41939    0.22705   1.847   0.0653 .  
## category_code_LT01_13_count  0.05773    0.24745   0.233   0.8156    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 0.619095069690606 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0197 -0.7912  0.0135  0.8972  3.4499 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94322    0.08836 112.535  < 2e-16 ***
## category_code_LT01_1_count   0.43552    0.08364   5.207 2.82e-07 ***
## category_code_LT01_2_count   0.81475    0.07246  11.244  < 2e-16 ***
## category_code_LT01_5_count   0.99779    0.06232  16.012  < 2e-16 ***
## category_code_LT01_8_count  -0.14785    0.27541  -0.537   0.5916    
## category_code_LT01_9_count   0.41183    0.22700   1.814   0.0702 .  
## category_code_LT01_14_count  0.09246    0.32977   0.280   0.7793    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 0.619105681933996 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0192 -0.8027  0.0218  0.8959  3.4519 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94126    0.08824 112.664  < 2e-16 ***
## category_code_LT01_1_count   0.44365    0.08444   5.254 2.22e-07 ***
## category_code_LT01_2_count   0.81879    0.07223  11.335  < 2e-16 ***
## category_code_LT01_5_count   0.99986    0.06188  16.159  < 2e-16 ***
## category_code_LT01_8_count  -0.14640    0.27540  -0.532   0.5952    
## category_code_LT01_9_count   0.41367    0.22665   1.825   0.0686 .  
## category_code_LT01_15_count -0.23226    0.76452  -0.304   0.7614    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 0.619094101066356 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0200 -0.7905  0.0136  0.9046  3.4510 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94211    0.08822 112.691  < 2e-16 ***
## category_code_LT01_1_count   0.43967    0.08293   5.302 1.74e-07 ***
## category_code_LT01_2_count   0.81443    0.07260  11.218  < 2e-16 ***
## category_code_LT01_5_count   0.99975    0.06188  16.156  < 2e-16 ***
## category_code_LT01_8_count  -0.15092    0.27575  -0.547   0.5844    
## category_code_LT01_9_count   0.41406    0.22664   1.827   0.0683 .  
## category_code_LT01_16_count  0.32744    1.17725   0.278   0.7810    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 0.625334747520155 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9972 -0.7719  0.0460  0.8781  3.4654 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92775    0.09090 109.211  < 2e-16 ***
## category_code_LT01_1_count   0.37609    0.08527   4.411 1.27e-05 ***
## category_code_LT01_2_count   0.66927    0.08723   7.672 9.16e-14 ***
## category_code_LT01_5_count   0.98756    0.06150  16.059  < 2e-16 ***
## category_code_LT01_8_count  -0.12069    0.27313  -0.442  0.65876    
## category_code_LT01_10_count  0.14287    0.11175   1.278  0.20170    
## category_code_LT01_11_count  0.35734    0.11548   3.094  0.00209 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6253 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 0.618030796199801 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9939 -0.7936  0.0121  0.9029  3.4828 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91032    0.09162 108.162  < 2e-16 ***
## category_code_LT01_1_count   0.44945    0.08357   5.378 1.17e-07 ***
## category_code_LT01_2_count   0.82668    0.07308  11.311  < 2e-16 ***
## category_code_LT01_5_count   1.00795    0.06208  16.237  < 2e-16 ***
## category_code_LT01_8_count  -0.13931    0.27586  -0.505    0.614    
## category_code_LT01_10_count  0.16227    0.11276   1.439    0.151    
## category_code_LT01_12_count -0.01085    0.20919  -0.052    0.959    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 0.61803163611245 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9937 -0.7937  0.0117  0.9041  3.4827 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91050    0.09163 108.162  < 2e-16 ***
## category_code_LT01_1_count   0.44799    0.08391   5.339 1.43e-07 ***
## category_code_LT01_2_count   0.82565    0.07189  11.485  < 2e-16 ***
## category_code_LT01_5_count   1.00742    0.06183  16.294  < 2e-16 ***
## category_code_LT01_8_count  -0.13872    0.27625  -0.502    0.616    
## category_code_LT01_10_count  0.16179    0.11273   1.435    0.152    
## category_code_LT01_13_count  0.01519    0.24739   0.061    0.951    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 0.618034078131443 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9941 -0.7943  0.0117  0.9050  3.4819 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91126    0.09220 107.501  < 2e-16 ***
## category_code_LT01_1_count   0.44785    0.08361   5.357 1.31e-07 ***
## category_code_LT01_2_count   0.82543    0.07199  11.466  < 2e-16 ***
## category_code_LT01_5_count   1.00699    0.06221  16.187  < 2e-16 ***
## category_code_LT01_8_count  -0.13996    0.27571  -0.508    0.612    
## category_code_LT01_10_count  0.15993    0.11546   1.385    0.167    
## category_code_LT01_14_count  0.02808    0.33774   0.083    0.934    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 0.618210069285238 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9917 -0.7887  0.0301  0.9045  3.4847 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90846    0.09168 108.079  < 2e-16 ***
## category_code_LT01_1_count   0.45661    0.08429   5.417 9.49e-08 ***
## category_code_LT01_2_count   0.82795    0.07182  11.528  < 2e-16 ***
## category_code_LT01_5_count   1.00746    0.06173  16.320  < 2e-16 ***
## category_code_LT01_8_count  -0.13922    0.27564  -0.505    0.614    
## category_code_LT01_10_count  0.16656    0.11303   1.474    0.141    
## category_code_LT01_15_count -0.37075    0.76768  -0.483    0.629    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6228, Adjusted R-squared:  0.6182 
## F-statistic: 135.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 0.618089924690978 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9941 -0.7941  0.0076  0.9052  3.4823 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91089    0.09162 108.172  < 2e-16 ***
## category_code_LT01_1_count   0.44977    0.08282   5.431 8.84e-08 ***
## category_code_LT01_2_count   0.82334    0.07232  11.385  < 2e-16 ***
## category_code_LT01_5_count   1.00747    0.06174  16.317  < 2e-16 ***
## category_code_LT01_8_count  -0.14373    0.27604  -0.521    0.603    
## category_code_LT01_10_count  0.16093    0.11272   1.428    0.154    
## category_code_LT01_16_count  0.33078    1.17903   0.281    0.779    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6227, Adjusted R-squared:  0.6181 
## F-statistic: 135.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 0.624486378435583 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0321 -0.7765  0.0355  0.8874  3.4339 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95923    0.08768 113.591  < 2e-16 ***
## category_code_LT01_1_count   0.37989    0.08560   4.438 1.12e-05 ***
## category_code_LT01_2_count   0.68571    0.08667   7.912 1.69e-14 ***
## category_code_LT01_5_count   0.99264    0.06176  16.072  < 2e-16 ***
## category_code_LT01_8_count  -0.10344    0.27357  -0.378  0.70550    
## category_code_LT01_11_count  0.38472    0.11846   3.248  0.00124 ** 
## category_code_LT01_12_count -0.15357    0.21267  -0.722  0.47057    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 0.6240876483265 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0293 -0.7485  0.0396  0.8970  3.4342 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.958912   0.087725 113.525  < 2e-16 ***
## category_code_LT01_1_count   0.375136   0.086393   4.342 1.71e-05 ***
## category_code_LT01_2_count   0.683487   0.086741   7.880 2.13e-14 ***
## category_code_LT01_5_count   0.988960   0.061661  16.039  < 2e-16 ***
## category_code_LT01_8_count  -0.111322   0.274003  -0.406  0.68471    
## category_code_LT01_11_count  0.365484   0.115559   3.163  0.00166 ** 
## category_code_LT01_13_count  0.002171   0.245402   0.009  0.99294    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6241 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 0.624176001626739 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0291 -0.7634  0.0456  0.8900  3.4327 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96050    0.08784 113.398  < 2e-16 ***
## category_code_LT01_1_count   0.37144    0.08613   4.312 1.95e-05 ***
## category_code_LT01_2_count   0.68076    0.08703   7.822 3.20e-14 ***
## category_code_LT01_5_count   0.98643    0.06204  15.900  < 2e-16 ***
## category_code_LT01_8_count  -0.11270    0.27348  -0.412  0.68046    
## category_code_LT01_11_count  0.36478    0.11550   3.158  0.00169 ** 
## category_code_LT01_14_count  0.11112    0.32695   0.340  0.73410    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6242 
## F-statistic: 138.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 0.62422937970836 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0284 -0.7477  0.0400  0.8945  3.4351 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95810    0.08773 113.515  < 2e-16 ***
## category_code_LT01_1_count   0.38191    0.08678   4.401 1.32e-05 ***
## category_code_LT01_2_count   0.68532    0.08675   7.900 1.84e-14 ***
## category_code_LT01_5_count   0.98885    0.06158  16.059  < 2e-16 ***
## category_code_LT01_8_count  -0.11067    0.27344  -0.405   0.6859    
## category_code_LT01_11_count  0.36655    0.11550   3.174   0.0016 ** 
## category_code_LT01_15_count -0.32676    0.75914  -0.430   0.6671    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6288, Adjusted R-squared:  0.6242 
## F-statistic: 138.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 0.624184600558836 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0295 -0.7488  0.0414  0.8994  3.4339 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95924    0.08772 113.540  < 2e-16 ***
## category_code_LT01_1_count   0.37635    0.08545   4.404  1.3e-05 ***
## category_code_LT01_2_count   0.67993    0.08724   7.794  3.9e-14 ***
## category_code_LT01_5_count   0.98877    0.06158  16.056  < 2e-16 ***
## category_code_LT01_8_count  -0.11650    0.27382  -0.425  0.67069    
## category_code_LT01_11_count  0.36581    0.11549   3.168  0.00163 ** 
## category_code_LT01_16_count  0.41615    1.16891   0.356  0.72198    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6242 
## F-statistic: 138.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 0.616429299756156 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0300 -0.7930  0.0003  0.9047  3.4477 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.945487   0.088511 112.364  < 2e-16 ***
## category_code_LT01_1_count   0.448179   0.084872   5.281 1.94e-07 ***
## category_code_LT01_2_count   0.845549   0.072168  11.716  < 2e-16 ***
## category_code_LT01_5_count   1.009364   0.062276  16.208  < 2e-16 ***
## category_code_LT01_8_count  -0.127955   0.276904  -0.462    0.644    
## category_code_LT01_12_count  0.001257   0.209462   0.006    0.995    
## category_code_LT01_13_count  0.027374   0.247773   0.110    0.912    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 0.616541835737331 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0300 -0.7945  0.0017  0.8885  3.4459 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.947288   0.088624 112.242  < 2e-16 ***
## category_code_LT01_1_count   0.445320   0.084463   5.272 2.02e-07 ***
## category_code_LT01_2_count   0.842862   0.072437  11.636  < 2e-16 ***
## category_code_LT01_5_count   1.006810   0.062618  16.079  < 2e-16 ***
## category_code_LT01_8_count  -0.131028   0.276339  -0.474    0.636    
## category_code_LT01_12_count -0.003582   0.209815  -0.017    0.986    
## category_code_LT01_14_count  0.130793   0.330824   0.395    0.693    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6165 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 0.616521650935027 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0295 -0.7968  0.0100  0.8991  3.4485 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.944673   0.088519 112.345  < 2e-16 ***
## category_code_LT01_1_count   0.455715   0.085373   5.338 1.44e-07 ***
## category_code_LT01_2_count   0.848280   0.072209  11.748  < 2e-16 ***
## category_code_LT01_5_count   1.009747   0.062187  16.237  < 2e-16 ***
## category_code_LT01_8_count  -0.129074   0.276340  -0.467    0.641    
## category_code_LT01_12_count -0.001776   0.209622  -0.008    0.993    
## category_code_LT01_15_count -0.277187   0.767442  -0.361    0.718    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6165 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 0.616504781041981 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0303 -0.7932 -0.0018  0.9060  3.4475 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.945704   0.088504 112.376  < 2e-16 ***
## category_code_LT01_1_count   0.450727   0.083794   5.379 1.16e-07 ***
## category_code_LT01_2_count   0.842817   0.072666  11.599  < 2e-16 ***
## category_code_LT01_5_count   1.009493   0.062192  16.232  < 2e-16 ***
## category_code_LT01_8_count  -0.134635   0.276715  -0.487    0.627    
## category_code_LT01_12_count  0.002621   0.209457   0.013    0.990    
## category_code_LT01_16_count  0.389609   1.180912   0.330    0.742    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6165 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616552013359692 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0298 -0.7946  0.0024  0.8902  3.4458 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94740    0.08863 112.239  < 2e-16 ***
## category_code_LT01_1_count   0.44351    0.08492   5.223 2.61e-07 ***
## category_code_LT01_2_count   0.84198    0.07127  11.815  < 2e-16 ***
## category_code_LT01_5_count   1.00632    0.06242  16.122  < 2e-16 ***
## category_code_LT01_8_count  -0.12921    0.27670  -0.467    0.641    
## category_code_LT01_13_count  0.02860    0.24774   0.115    0.908    
## category_code_LT01_14_count  0.13091    0.33022   0.396    0.692    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616526401513362 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0293 -0.7940  0.0094  0.9019  3.4484 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94476    0.08852 112.342  < 2e-16 ***
## category_code_LT01_1_count   0.45440    0.08587   5.292 1.83e-07 ***
## category_code_LT01_2_count   0.84769    0.07091  11.955  < 2e-16 ***
## category_code_LT01_5_count   1.00944    0.06193  16.298  < 2e-16 ***
## category_code_LT01_8_count  -0.12782    0.27669  -0.462    0.644    
## category_code_LT01_13_count  0.01951    0.24873   0.078    0.938    
## category_code_LT01_15_count -0.27148    0.76982  -0.353    0.724    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6165 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 0.616516242590618 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0302 -0.7933 -0.0096  0.9065  3.4474 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94580    0.08850 112.376  < 2e-16 ***
## category_code_LT01_1_count   0.44919    0.08413   5.340 1.43e-07 ***
## category_code_LT01_2_count   0.84230    0.07137  11.801  < 2e-16 ***
## category_code_LT01_5_count   1.00918    0.06194  16.293  < 2e-16 ***
## category_code_LT01_8_count  -0.13248    0.27704  -0.478    0.633    
## category_code_LT01_13_count  0.03019    0.24787   0.122    0.903    
## category_code_LT01_16_count  0.39424    1.18142   0.334    0.739    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6165 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 0.61664189664465 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0292 -0.7938  0.0156  0.8871  3.4466 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94657    0.08863 112.220  < 2e-16 ***
## category_code_LT01_1_count   0.45094    0.08529   5.287 1.87e-07 ***
## category_code_LT01_2_count   0.84454    0.07124  11.855  < 2e-16 ***
## category_code_LT01_5_count   1.00666    0.06232  16.153  < 2e-16 ***
## category_code_LT01_8_count  -0.13055    0.27615  -0.473    0.637    
## category_code_LT01_14_count  0.12960    0.33017   0.393    0.695    
## category_code_LT01_15_count -0.27475    0.76662  -0.358    0.720    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 0.616638413814283 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0301 -0.7905 -0.0093  0.8954  3.4454 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94771    0.08862 112.251  < 2e-16 ***
## category_code_LT01_1_count   0.44607    0.08378   5.324 1.55e-07 ***
## category_code_LT01_2_count   0.83898    0.07179  11.687  < 2e-16 ***
## category_code_LT01_5_count   1.00636    0.06233  16.146  < 2e-16 ***
## category_code_LT01_8_count  -0.13630    0.27652  -0.493    0.622    
## category_code_LT01_14_count  0.13686    0.33066   0.414    0.679    
## category_code_LT01_16_count  0.41632    1.18235   0.352    0.725    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 0.616600798501361 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0296 -0.7938  0.0073  0.8986  3.4482 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94499    0.08851 112.356  < 2e-16 ***
## category_code_LT01_1_count   0.45650    0.08451   5.402 1.03e-07 ***
## category_code_LT01_2_count   0.84497    0.07135  11.842  < 2e-16 ***
## category_code_LT01_5_count   1.00951    0.06185  16.323  < 2e-16 ***
## category_code_LT01_8_count  -0.13373    0.27651  -0.484    0.629    
## category_code_LT01_15_count -0.26914    0.76703  -0.351    0.726    
## category_code_LT01_16_count  0.37620    1.18121   0.318    0.750    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.626902146849334 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9890 -0.7662  0.0782  0.8804  3.4652 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92794    0.09070 109.460  < 2e-16 ***
## category_code_LT01_1_count   0.36730    0.08514   4.314 1.94e-05 ***
## category_code_LT01_2_count   0.65194    0.08778   7.427 4.96e-13 ***
## category_code_LT01_5_count   0.97549    0.06080  16.043  < 2e-16 ***
## category_code_LT01_9_count   0.33985    0.22613   1.503  0.13350    
## category_code_LT01_10_count  0.12140    0.11229   1.081  0.28016    
## category_code_LT01_11_count  0.34886    0.11539   3.023  0.00263 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6314, Adjusted R-squared:  0.6269 
## F-statistic: 140.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 0.61995961326624 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9847 -0.7767  0.0384  0.9204  3.4822 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91094    0.09138 108.462  < 2e-16 ***
## category_code_LT01_1_count   0.43782    0.08354   5.241 2.38e-07 ***
## category_code_LT01_2_count   0.80343    0.07429  10.815  < 2e-16 ***
## category_code_LT01_5_count   0.99390    0.06144  16.176  < 2e-16 ***
## category_code_LT01_9_count   0.37776    0.22787   1.658    0.098 .  
## category_code_LT01_10_count  0.13789    0.11330   1.217    0.224    
## category_code_LT01_12_count -0.01291    0.20854  -0.062    0.951    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6245, Adjusted R-squared:   0.62 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 0.619992394347087 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9845 -0.7790  0.0422  0.9222  3.4817 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91143    0.09138 108.464  < 2e-16 ***
## category_code_LT01_1_count   0.43406    0.08390   5.174 3.35e-07 ***
## category_code_LT01_2_count   0.80126    0.07319  10.948  < 2e-16 ***
## category_code_LT01_5_count   0.99285    0.06114  16.238  < 2e-16 ***
## category_code_LT01_9_count   0.38140    0.22847   1.669   0.0957 .  
## category_code_LT01_10_count  0.13659    0.11329   1.206   0.2285    
## category_code_LT01_13_count  0.05307    0.24692   0.215   0.8299    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:   0.62 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 0.619956846703851 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9846 -0.7872  0.0380  0.9234  3.4820 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.911196   0.091945 107.795  < 2e-16 ***
## category_code_LT01_1_count  0.436902   0.083528   5.231 2.51e-07 ***
## category_code_LT01_2_count  0.802465   0.073164  10.968  < 2e-16 ***
## category_code_LT01_5_count  0.993365   0.061521  16.147  < 2e-16 ***
## category_code_LT01_9_count  0.377683   0.228036   1.656   0.0983 .  
## category_code_LT01_10_count 0.137199   0.115862   1.184   0.2369    
## category_code_LT01_14_count 0.005433   0.337130   0.016   0.9871    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6245, Adjusted R-squared:   0.62 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 0.62009080312559 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9829 -0.7910  0.0453  0.9122  3.4838 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90935    0.09144 108.372  < 2e-16 ***
## category_code_LT01_1_count   0.44389    0.08429   5.266 2.09e-07 ***
## category_code_LT01_2_count   0.80452    0.07309  11.008  < 2e-16 ***
## category_code_LT01_5_count   0.99347    0.06106  16.270  < 2e-16 ***
## category_code_LT01_9_count   0.37380    0.22803   1.639    0.102    
## category_code_LT01_10_count  0.14175    0.11361   1.248    0.213    
## category_code_LT01_15_count -0.31915    0.76647  -0.416    0.677    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6247, Adjusted R-squared:  0.6201 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 0.619991263829676 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9848 -0.7868  0.0403  0.9225  3.4818 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91138    0.09138 108.468  < 2e-16 ***
## category_code_LT01_1_count   0.43779    0.08277   5.289 1.85e-07 ***
## category_code_LT01_2_count   0.80068    0.07348  10.896  < 2e-16 ***
## category_code_LT01_5_count   0.99330    0.06108  16.263  < 2e-16 ***
## category_code_LT01_9_count   0.37656    0.22794   1.652   0.0992 .  
## category_code_LT01_10_count  0.13682    0.11325   1.208   0.2276    
## category_code_LT01_16_count  0.24850    1.17498   0.211   0.8326    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:   0.62 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.626406241003075 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0189 -0.7748  0.0606  0.8634  3.4386 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95460    0.08745 113.833  < 2e-16 ***
## category_code_LT01_1_count   0.37084    0.08544   4.340 1.73e-05 ***
## category_code_LT01_2_count   0.66475    0.08736   7.609 1.42e-13 ***
## category_code_LT01_5_count   0.98025    0.06109  16.046  < 2e-16 ***
## category_code_LT01_9_count   0.36691    0.22467   1.633  0.10310    
## category_code_LT01_11_count  0.37385    0.11834   3.159  0.00168 ** 
## category_code_LT01_12_count -0.15220    0.21197  -0.718  0.47308    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6309, Adjusted R-squared:  0.6264 
## F-statistic: 139.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.626031131184183 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0156 -0.7897  0.0682  0.8506  3.4389 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95429    0.08749 113.772  < 2e-16 ***
## category_code_LT01_1_count   0.36412    0.08623   4.223 2.88e-05 ***
## category_code_LT01_2_count   0.66175    0.08747   7.566 1.92e-13 ***
## category_code_LT01_5_count   0.97588    0.06093  16.016  < 2e-16 ***
## category_code_LT01_9_count   0.37146    0.22533   1.649  0.09989 .  
## category_code_LT01_11_count  0.35415    0.11548   3.067  0.00228 ** 
## category_code_LT01_13_count  0.03679    0.24492   0.150  0.88066    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.626055117334288 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0157 -0.7904  0.0706  0.8504  3.4379 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95530    0.08762 113.620  < 2e-16 ***
## category_code_LT01_1_count   0.36354    0.08593   4.231 2.78e-05 ***
## category_code_LT01_2_count   0.66073    0.08765   7.538 2.32e-13 ***
## category_code_LT01_5_count   0.97459    0.06131  15.897  < 2e-16 ***
## category_code_LT01_9_count   0.36578    0.22521   1.624  0.10498    
## category_code_LT01_11_count  0.35442    0.11540   3.071  0.00225 ** 
## category_code_LT01_14_count  0.07597    0.32675   0.233  0.81624    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6306, Adjusted R-squared:  0.6261 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.626123992565741 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0151 -0.7889  0.0666  0.8460  3.4396 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95351    0.08750 113.757  < 2e-16 ***
## category_code_LT01_1_count   0.37203    0.08664   4.294 2.12e-05 ***
## category_code_LT01_2_count   0.66418    0.08746   7.594 1.57e-13 ***
## category_code_LT01_5_count   0.97626    0.06086  16.040  < 2e-16 ***
## category_code_LT01_9_count   0.36624    0.22486   1.629  0.10401    
## category_code_LT01_11_count  0.35580    0.11541   3.083  0.00216 ** 
## category_code_LT01_15_count -0.28801    0.75762  -0.380  0.70399    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6306, Adjusted R-squared:  0.6261 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.62607557403253 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0158 -0.7898  0.0698  0.8501  3.4387 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95444    0.08749 113.778  < 2e-16 ***
## category_code_LT01_1_count   0.36695    0.08528   4.303 2.04e-05 ***
## category_code_LT01_2_count   0.65967    0.08788   7.506 2.88e-13 ***
## category_code_LT01_5_count   0.97602    0.06087  16.033  < 2e-16 ***
## category_code_LT01_9_count   0.36708    0.22486   1.632   0.1032    
## category_code_LT01_11_count  0.35515    0.11539   3.078   0.0022 ** 
## category_code_LT01_16_count  0.33140    1.16497   0.284   0.7762    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6306, Adjusted R-squared:  0.6261 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 0.618867518353111 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.8088  0.0210  0.9074  3.4524 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.940744   0.088216 112.686  < 2e-16 ***
## category_code_LT01_1_count   0.433490   0.084815   5.111  4.6e-07 ***
## category_code_LT01_2_count   0.815856   0.073759  11.061  < 2e-16 ***
## category_code_LT01_5_count   0.994037   0.061597  16.138  < 2e-16 ***
## category_code_LT01_9_count   0.415862   0.227008   1.832   0.0676 .  
## category_code_LT01_12_count -0.002701   0.208664  -0.013   0.9897    
## category_code_LT01_13_count  0.065446   0.247081   0.265   0.7912    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 0.618872095580285 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0150 -0.8076  0.0215  0.9094  3.4513 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.941866   0.088347 112.532  < 2e-16 ***
## category_code_LT01_1_count   0.434242   0.084336   5.149  3.8e-07 ***
## category_code_LT01_2_count   0.815557   0.073836  11.046  < 2e-16 ***
## category_code_LT01_5_count   0.992871   0.061931  16.032  < 2e-16 ***
## category_code_LT01_9_count   0.407750   0.226940   1.797    0.073 .  
## category_code_LT01_12_count -0.005785   0.209055  -0.028    0.978    
## category_code_LT01_14_count  0.091140   0.330475   0.276    0.783    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 0.618886902525529 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0144 -0.8082  0.0329  0.9060  3.4532 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.939930   0.088230 112.659  < 2e-16 ***
## category_code_LT01_1_count   0.442384   0.085326   5.185 3.17e-07 ***
## category_code_LT01_2_count   0.819536   0.073758  11.111  < 2e-16 ***
## category_code_LT01_5_count   0.994928   0.061525  16.171  < 2e-16 ***
## category_code_LT01_9_count   0.409534   0.226586   1.807   0.0713 .  
## category_code_LT01_12_count -0.004998   0.208845  -0.024   0.9809    
## category_code_LT01_15_count -0.236092   0.765433  -0.308   0.7579    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 0.618861761723222 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0150 -0.8033  0.0278  0.9166  3.4524 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.940735   0.088217 112.685  < 2e-16 ***
## category_code_LT01_1_count   0.437980   0.083713   5.232 2.49e-07 ***
## category_code_LT01_2_count   0.815176   0.074092  11.002  < 2e-16 ***
## category_code_LT01_5_count   0.994573   0.061534  16.163  < 2e-16 ***
## category_code_LT01_9_count   0.410022   0.226584   1.810    0.071 .  
## category_code_LT01_12_count -0.001472   0.208679  -0.007    0.994    
## category_code_LT01_16_count  0.294624   1.176217   0.250    0.802    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 0.618926912877554 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0145 -0.8044  0.0284  0.9110  3.4510 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94211    0.08834 112.538  < 2e-16 ***
## category_code_LT01_1_count   0.43015    0.08480   5.073 5.58e-07 ***
## category_code_LT01_2_count   0.81340    0.07277  11.177  < 2e-16 ***
## category_code_LT01_5_count   0.99187    0.06168  16.081  < 2e-16 ***
## category_code_LT01_9_count   0.41188    0.22744   1.811   0.0708 .  
## category_code_LT01_13_count  0.06602    0.24706   0.267   0.7894    
## category_code_LT01_14_count  0.09134    0.32983   0.277   0.7819    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 0.618930185396117 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0141 -0.8082  0.0289  0.9067  3.4530 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94019    0.08823 112.662  < 2e-16 ***
## category_code_LT01_1_count   0.43837    0.08585   5.106 4.71e-07 ***
## category_code_LT01_2_count   0.81749    0.07259  11.261  < 2e-16 ***
## category_code_LT01_5_count   0.99404    0.06122  16.237  < 2e-16 ***
## category_code_LT01_9_count   0.41339    0.22715   1.820   0.0694 .  
## category_code_LT01_13_count  0.05889    0.24811   0.237   0.8125    
## category_code_LT01_15_count -0.21845    0.76797  -0.284   0.7762    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 0.618919870646164 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.8064  0.0235  0.9091  3.4522 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94098    0.08821 112.692  < 2e-16 ***
## category_code_LT01_1_count   0.43407    0.08406   5.164 3.52e-07 ***
## category_code_LT01_2_count   0.81319    0.07294  11.150  < 2e-16 ***
## category_code_LT01_5_count   0.99369    0.06123  16.229  < 2e-16 ***
## category_code_LT01_9_count   0.41420    0.22708   1.824   0.0688 .  
## category_code_LT01_13_count  0.06766    0.24721   0.274   0.7844    
## category_code_LT01_16_count  0.30599    1.17672   0.260   0.7949    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 0.618944330006932 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0143 -0.8090  0.0292  0.9104  3.4519 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94128    0.08836 112.510  < 2e-16 ***
## category_code_LT01_1_count   0.43895    0.08519   5.153 3.73e-07 ***
## category_code_LT01_2_count   0.81695    0.07270  11.237  < 2e-16 ***
## category_code_LT01_5_count   0.99272    0.06160  16.116  < 2e-16 ***
## category_code_LT01_9_count   0.40559    0.22703   1.786   0.0746 .  
## category_code_LT01_14_count  0.09006    0.32982   0.273   0.7849    
## category_code_LT01_15_count -0.23425    0.76467  -0.306   0.7595    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 0.618926644918049 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0149 -0.8054  0.0264  0.9098  3.4510 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94217    0.08835 112.535  < 2e-16 ***
## category_code_LT01_1_count   0.43465    0.08365   5.196 2.99e-07 ***
## category_code_LT01_2_count   0.81256    0.07313  11.112  < 2e-16 ***
## category_code_LT01_5_count   0.99234    0.06162  16.105  < 2e-16 ***
## category_code_LT01_9_count   0.40571    0.22706   1.787   0.0746 .  
## category_code_LT01_14_count  0.09554    0.33035   0.289   0.7725    
## category_code_LT01_16_count  0.31397    1.17787   0.267   0.7899    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 0.618931673159978 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0144 -0.8052  0.0319  0.9114  3.4530 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94016    0.08823 112.664  < 2e-16 ***
## category_code_LT01_1_count   0.44276    0.08446   5.243 2.36e-07 ***
## category_code_LT01_2_count   0.81690    0.07286  11.211  < 2e-16 ***
## category_code_LT01_5_count   0.99455    0.06115  16.263  < 2e-16 ***
## category_code_LT01_9_count   0.40792    0.22667   1.800   0.0725 .  
## category_code_LT01_15_count -0.22967    0.76503  -0.300   0.7641    
## category_code_LT01_16_count  0.28398    1.17653   0.241   0.8094    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.625647465336799 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9961 -0.7844  0.0572  0.8817  3.4664 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92680    0.09085 109.266  < 2e-16 ***
## category_code_LT01_1_count   0.37954    0.08540   4.444 1.09e-05 ***
## category_code_LT01_2_count   0.67111    0.08724   7.693 7.93e-14 ***
## category_code_LT01_5_count   0.98744    0.06093  16.207  < 2e-16 ***
## category_code_LT01_10_count  0.14421    0.11172   1.291  0.19736    
## category_code_LT01_11_count  0.37892    0.11835   3.202  0.00146 ** 
## category_code_LT01_12_count -0.16518    0.21226  -0.778  0.43682    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6256 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.625185761375972 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9934 -0.7766  0.0401  0.8889  3.4662 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.926954   0.090919 109.184  < 2e-16 ***
## category_code_LT01_1_count   0.374493   0.086153   4.347 1.68e-05 ***
## category_code_LT01_2_count   0.669004   0.087310   7.662 9.82e-14 ***
## category_code_LT01_5_count   0.983248   0.060769  16.180  < 2e-16 ***
## category_code_LT01_10_count  0.141584   0.111790   1.267  0.20593    
## category_code_LT01_11_count  0.358511   0.115536   3.103  0.00203 ** 
## category_code_LT01_13_count -0.001292   0.244699  -0.005  0.99579    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6297, Adjusted R-squared:  0.6252 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.625188454368795 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9937 -0.7766  0.0422  0.8912  3.4656 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92757    0.09148 108.523  < 2e-16 ***
## category_code_LT01_1_count   0.37373    0.08600   4.346 1.69e-05 ***
## category_code_LT01_2_count   0.66864    0.08744   7.647 1.09e-13 ***
## category_code_LT01_5_count   0.98279    0.06119  16.061  < 2e-16 ***
## category_code_LT01_10_count  0.14007    0.11450   1.223  0.22179    
## category_code_LT01_11_count  0.35845    0.11548   3.104  0.00202 ** 
## category_code_LT01_14_count  0.01995    0.33456   0.060  0.95247    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6297, Adjusted R-squared:  0.6252 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.625408017895637 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9911 -0.7661  0.0415  0.8916  3.4683 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92488    0.09096 109.112  < 2e-16 ***
## category_code_LT01_1_count   0.38283    0.08659   4.421 1.21e-05 ***
## category_code_LT01_2_count   0.67076    0.08728   7.685 8.40e-14 ***
## category_code_LT01_5_count   0.98304    0.06071  16.193  < 2e-16 ***
## category_code_LT01_10_count  0.14653    0.11208   1.307  0.19170    
## category_code_LT01_11_count  0.35949    0.11546   3.114  0.00196 ** 
## category_code_LT01_15_count -0.41049    0.76050  -0.540  0.58960    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6254 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.625249422337331 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9937 -0.7766  0.0448  0.8931  3.4657 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.92746    0.09091 109.196  < 2e-16 ***
## category_code_LT01_1_count   0.37526    0.08524   4.402 1.32e-05 ***
## category_code_LT01_2_count   0.66618    0.08778   7.589 1.63e-13 ***
## category_code_LT01_5_count   0.98293    0.06073  16.186  < 2e-16 ***
## category_code_LT01_10_count  0.14038    0.11180   1.256    0.210    
## category_code_LT01_11_count  0.35884    0.11547   3.108    0.002 ** 
## category_code_LT01_16_count  0.33694    1.16648   0.289    0.773    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6252 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 0.617839248363076 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9895 -0.7914  0.0261  0.9014  3.4837 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90949    0.09164 108.131  < 2e-16 ***
## category_code_LT01_1_count   0.44673    0.08463   5.278 1.96e-07 ***
## category_code_LT01_2_count   0.82672    0.07326  11.285  < 2e-16 ***
## category_code_LT01_5_count   1.00291    0.06141  16.331  < 2e-16 ***
## category_code_LT01_10_count  0.16057    0.11282   1.423    0.155    
## category_code_LT01_12_count -0.01457    0.20913  -0.070    0.944    
## category_code_LT01_13_count  0.02314    0.24697   0.094    0.925    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6178 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 0.617837802728887 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9900 -0.8013  0.0277  0.9041  3.4830 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91018    0.09220 107.481  < 2e-16 ***
## category_code_LT01_1_count   0.44706    0.08430   5.303 1.73e-07 ***
## category_code_LT01_2_count   0.82672    0.07330  11.279  < 2e-16 ***
## category_code_LT01_5_count   1.00254    0.06179  16.225  < 2e-16 ***
## category_code_LT01_10_count  0.15883    0.11551   1.375    0.170    
## category_code_LT01_12_count -0.01537    0.20943  -0.073    0.942    
## category_code_LT01_14_count  0.02814    0.33831   0.083    0.934    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6178 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 0.618018284096728 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9876 -0.7893  0.0393  0.9001  3.4858 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90733    0.09170 108.047  < 2e-16 ***
## category_code_LT01_1_count   0.45615    0.08517   5.356 1.31e-07 ***
## category_code_LT01_2_count   0.82952    0.07324  11.327  < 2e-16 ***
## category_code_LT01_5_count   1.00316    0.06134  16.353  < 2e-16 ***
## category_code_LT01_10_count  0.16562    0.11314   1.464    0.144    
## category_code_LT01_12_count -0.01922    0.20930  -0.092    0.927    
## category_code_LT01_15_count -0.37573    0.76870  -0.489    0.625    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 0.617882337585894 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9898 -0.7922  0.0238  0.9016  3.4834 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90975    0.09164 108.142  < 2e-16 ***
## category_code_LT01_1_count   0.44875    0.08359   5.368 1.23e-07 ***
## category_code_LT01_2_count   0.82477    0.07371  11.190  < 2e-16 ***
## category_code_LT01_5_count   1.00286    0.06137  16.342  < 2e-16 ***
## category_code_LT01_10_count  0.15986    0.11283   1.417    0.157    
## category_code_LT01_12_count -0.01359    0.20914  -0.065    0.948    
## category_code_LT01_16_count  0.29834    1.17797   0.253    0.800    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6179 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 0.617840611299012 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9897 -0.7927  0.0234  0.8992  3.4827 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91044    0.09222 107.464  < 2e-16 ***
## category_code_LT01_1_count   0.44493    0.08472   5.252 2.25e-07 ***
## category_code_LT01_2_count   0.82523    0.07219  11.432  < 2e-16 ***
## category_code_LT01_5_count   1.00181    0.06153  16.283  < 2e-16 ***
## category_code_LT01_10_count  0.15818    0.11554   1.369    0.172    
## category_code_LT01_13_count  0.02343    0.24701   0.095    0.924    
## category_code_LT01_14_count  0.02747    0.33789   0.081    0.935    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6178 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 0.618013535696687 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9873 -0.7894  0.0362  0.8939  3.4856 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90759    0.09171 108.036  < 2e-16 ***
## category_code_LT01_1_count   0.45427    0.08561   5.306  1.7e-07 ***
## category_code_LT01_2_count   0.82795    0.07204  11.493  < 2e-16 ***
## category_code_LT01_5_count   1.00242    0.06103  16.425  < 2e-16 ***
## category_code_LT01_10_count  0.16492    0.11311   1.458    0.145    
## category_code_LT01_13_count  0.01196    0.24798   0.048    0.962    
## category_code_LT01_15_count -0.36896    0.77122  -0.478    0.633    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617887299593384 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9896 -0.7918  0.0244  0.8977  3.4831 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91004    0.09164 108.138  < 2e-16 ***
## category_code_LT01_1_count   0.44660    0.08387   5.325 1.54e-07 ***
## category_code_LT01_2_count   0.82330    0.07253  11.352  < 2e-16 ***
## category_code_LT01_5_count   1.00215    0.06105  16.415  < 2e-16 ***
## category_code_LT01_10_count  0.15916    0.11279   1.411    0.159    
## category_code_LT01_13_count  0.02544    0.24712   0.103    0.918    
## category_code_LT01_16_count  0.30418    1.17867   0.258    0.796    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6179 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 0.61801519312512 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9876 -0.7899  0.0381  0.8948  3.4850 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90818    0.09228 107.375  < 2e-16 ***
## category_code_LT01_1_count   0.45418    0.08515   5.334 1.47e-07 ***
## category_code_LT01_2_count   0.82779    0.07212  11.479  < 2e-16 ***
## category_code_LT01_5_count   1.00204    0.06145  16.306  < 2e-16 ***
## category_code_LT01_10_count  0.16344    0.11587   1.411    0.159    
## category_code_LT01_14_count  0.02256    0.33786   0.067    0.947    
## category_code_LT01_15_count -0.37110    0.76812  -0.483    0.629    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617886187665634 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9900 -0.7942  0.0246  0.9006  3.4823 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.91085    0.09222 107.466  < 2e-16 ***
## category_code_LT01_1_count   0.44686    0.08360   5.345 1.38e-07 ***
## category_code_LT01_2_count   0.82320    0.07265  11.331  < 2e-16 ***
## category_code_LT01_5_count   1.00168    0.06148  16.293  < 2e-16 ***
## category_code_LT01_10_count  0.15710    0.11559   1.359    0.175    
## category_code_LT01_14_count  0.03242    0.33849   0.096    0.924    
## category_code_LT01_16_count  0.30677    1.18022   0.260    0.795    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6179 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 0.618055701504614 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9875 -0.7897  0.0339  0.8941  3.4852 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.90792    0.09169 108.055  < 2e-16 ***
## category_code_LT01_1_count   0.45562    0.08428   5.406 1.01e-07 ***
## category_code_LT01_2_count   0.82597    0.07245  11.400  < 2e-16 ***
## category_code_LT01_5_count   1.00231    0.06098  16.436  < 2e-16 ***
## category_code_LT01_10_count  0.16410    0.11310   1.451    0.147    
## category_code_LT01_15_count -0.36612    0.76828  -0.477    0.634    
## category_code_LT01_16_count  0.28015    1.17826   0.238    0.812    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6227, Adjusted R-squared:  0.6181 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.62437795243157 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0287 -0.7812  0.0405  0.8688  3.4348 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.958346   0.087660 113.602  < 2e-16 ***
## category_code_LT01_1_count   0.378126   0.086489   4.372 1.50e-05 ***
## category_code_LT01_2_count   0.685277   0.086754   7.899 1.86e-14 ***
## category_code_LT01_5_count   0.988918   0.061065  16.195  < 2e-16 ***
## category_code_LT01_11_count  0.385922   0.118489   3.257   0.0012 ** 
## category_code_LT01_12_count -0.156846   0.212524  -0.738   0.4609    
## category_code_LT01_13_count  0.008492   0.244845   0.035   0.9723    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6289, Adjusted R-squared:  0.6244 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.624486836558966 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0286 -0.7957  0.0479  0.8664  3.4331 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96009    0.08777 113.481  < 2e-16 ***
## category_code_LT01_1_count   0.37444    0.08622   4.343 1.71e-05 ***
## category_code_LT01_2_count   0.68239    0.08703   7.841 2.80e-14 ***
## category_code_LT01_5_count   0.98622    0.06145  16.049  < 2e-16 ***
## category_code_LT01_11_count  0.38584    0.11841   3.259   0.0012 ** 
## category_code_LT01_12_count -0.16161    0.21287  -0.759   0.4481    
## category_code_LT01_14_count  0.12404    0.32736   0.379   0.7049    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.624546017165167 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0279 -0.7738  0.0375  0.8540  3.4357 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95746    0.08766 113.598  < 2e-16 ***
## category_code_LT01_1_count   0.38601    0.08698   4.438 1.12e-05 ***
## category_code_LT01_2_count   0.68745    0.08677   7.923 1.57e-14 ***
## category_code_LT01_5_count   0.98901    0.06100  16.212  < 2e-16 ***
## category_code_LT01_11_count  0.38778    0.11846   3.274  0.00114 ** 
## category_code_LT01_12_count -0.16173    0.21273  -0.760  0.44746    
## category_code_LT01_15_count -0.35714    0.75971  -0.470  0.63850    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.624457947397817 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0287 -0.7773  0.0445  0.8672  3.4346 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95858    0.08765 113.617  < 2e-16 ***
## category_code_LT01_1_count   0.37948    0.08558   4.434 1.14e-05 ***
## category_code_LT01_2_count   0.68210    0.08726   7.817 3.33e-14 ***
## category_code_LT01_5_count   0.98862    0.06102  16.201  < 2e-16 ***
## category_code_LT01_11_count  0.38626    0.11841   3.262  0.00118 ** 
## category_code_LT01_12_count -0.15596    0.21252  -0.734  0.46339    
## category_code_LT01_16_count  0.37958    1.16702   0.325  0.74513    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.624047153718606 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0253 -0.7726  0.0443  0.8892  3.4336 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.959509   0.087821 113.407  < 2e-16 ***
## category_code_LT01_1_count  0.369457   0.087035   4.245 2.62e-05 ***
## category_code_LT01_2_count  0.680276   0.087122   7.808 3.53e-14 ***
## category_code_LT01_5_count  0.982321   0.061332  16.016  < 2e-16 ***
## category_code_LT01_11_count 0.365651   0.115565   3.164  0.00165 ** 
## category_code_LT01_13_count 0.009414   0.244976   0.038  0.96936    
## category_code_LT01_14_count 0.109517   0.327013   0.335  0.73784    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.624 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.624104048152819 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0247 -0.7467  0.0450  0.8698  3.4360 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.957111   0.087712 113.521  < 2e-16 ***
## category_code_LT01_1_count   0.380517   0.087880   4.330 1.81e-05 ***
## category_code_LT01_2_count   0.684974   0.086850   7.887 2.03e-14 ***
## category_code_LT01_5_count   0.984879   0.060843  16.187  < 2e-16 ***
## category_code_LT01_11_count  0.367565   0.115568   3.181  0.00156 ** 
## category_code_LT01_13_count -0.001351   0.245950  -0.005  0.99562    
## category_code_LT01_15_count -0.329237   0.762395  -0.432  0.66604    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6241 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.624047679664812 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0255 -0.7604  0.0477  0.8905  3.4349 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95823    0.08770 113.547  < 2e-16 ***
## category_code_LT01_1_count   0.37411    0.08631   4.334 1.77e-05 ***
## category_code_LT01_2_count   0.67956    0.08734   7.780 4.30e-14 ***
## category_code_LT01_5_count   0.98449    0.06086  16.176  < 2e-16 ***
## category_code_LT01_11_count  0.36666    0.11555   3.173   0.0016 ** 
## category_code_LT01_13_count  0.01131    0.24512   0.046   0.9632    
## category_code_LT01_16_count  0.39248    1.16835   0.336   0.7371    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.624 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.624188010258183 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0244 -0.7612  0.0361  0.8768  3.4345 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95866    0.08782 113.398  < 2e-16 ***
## category_code_LT01_1_count   0.37667    0.08746   4.307 2.00e-05 ***
## category_code_LT01_2_count   0.68225    0.08713   7.831 3.02e-14 ***
## category_code_LT01_5_count   0.98233    0.06127  16.033  < 2e-16 ***
## category_code_LT01_11_count  0.36683    0.11550   3.176  0.00159 ** 
## category_code_LT01_14_count  0.10830    0.32693   0.331  0.74060    
## category_code_LT01_15_count -0.32698    0.75918  -0.431  0.66687    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6242 
## F-statistic: 138.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.624141488583504 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0253 -0.7730  0.0401  0.8881  3.4333 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95985    0.08781 113.422  < 2e-16 ***
## category_code_LT01_1_count   0.37076    0.08609   4.307 2.00e-05 ***
## category_code_LT01_2_count   0.67668    0.08767   7.719 6.64e-14 ***
## category_code_LT01_5_count   0.98188    0.06129  16.019  < 2e-16 ***
## category_code_LT01_11_count  0.36610    0.11549   3.170  0.00162 ** 
## category_code_LT01_14_count  0.11561    0.32742   0.353  0.72417    
## category_code_LT01_16_count  0.41287    1.16914   0.353  0.72413    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6241 
## F-statistic: 138.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.624182961363418 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0247 -0.7470  0.0475  0.8767  3.4358 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95740    0.08770 113.538  < 2e-16 ***
## category_code_LT01_1_count   0.38121    0.08675   4.395 1.36e-05 ***
## category_code_LT01_2_count   0.68166    0.08735   7.804 3.65e-14 ***
## category_code_LT01_5_count   0.98451    0.06080  16.192  < 2e-16 ***
## category_code_LT01_11_count  0.36783    0.11549   3.185  0.00154 ** 
## category_code_LT01_15_count -0.32123    0.75954  -0.423  0.67253    
## category_code_LT01_16_count  0.37506    1.16792   0.321  0.74824    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6242 
## F-statistic: 138.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616382656514628 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0256 -0.7940  0.0064  0.8917  3.4470 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.946205   0.088610 112.247  < 2e-16 ***
## category_code_LT01_1_count   0.442022   0.085544   5.167 3.46e-07 ***
## category_code_LT01_2_count   0.842429   0.072652  11.595  < 2e-16 ***
## category_code_LT01_5_count   1.001926   0.061966  16.169  < 2e-16 ***
## category_code_LT01_12_count -0.007266   0.209745  -0.035    0.972    
## category_code_LT01_13_count  0.035837   0.247329   0.145    0.885    
## category_code_LT01_14_count  0.129774   0.330905   0.392    0.695    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616360248482971 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0251 -0.7987  0.0157  0.8804  3.4496 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.943597   0.088508 112.346  < 2e-16 ***
## category_code_LT01_1_count   0.452808   0.086679   5.224 2.59e-07 ***
## category_code_LT01_2_count   0.847979   0.072461  11.703  < 2e-16 ***
## category_code_LT01_5_count   1.005001   0.061516  16.337  < 2e-16 ***
## category_code_LT01_12_count -0.005328   0.209539  -0.025    0.980    
## category_code_LT01_13_count  0.026635   0.248315   0.107    0.915    
## category_code_LT01_15_count -0.272606   0.770688  -0.354    0.724    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.616337672738308 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0257 -0.7972  0.0062  0.8918  3.4486 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.944592   0.088491 112.380  < 2e-16 ***
## category_code_LT01_1_count   0.447216   0.084835   5.272 2.03e-07 ***
## category_code_LT01_2_count   0.842533   0.072895  11.558  < 2e-16 ***
## category_code_LT01_5_count   1.004468   0.061529  16.325  < 2e-16 ***
## category_code_LT01_12_count -0.001269   0.209376  -0.006    0.995    
## category_code_LT01_13_count  0.037342   0.247488   0.151    0.880    
## category_code_LT01_16_count  0.366133   1.180355   0.310    0.757    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6163 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616469263842759 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0250 -0.7936  0.0211  0.8848  3.4478 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94533    0.08862 112.229  < 2e-16 ***
## category_code_LT01_1_count   0.45008    0.08607   5.230 2.52e-07 ***
## category_code_LT01_2_count   0.84539    0.07269  11.631  < 2e-16 ***
## category_code_LT01_5_count   1.00238    0.06190  16.193  < 2e-16 ***
## category_code_LT01_12_count -0.01024    0.20990  -0.049    0.961    
## category_code_LT01_14_count  0.12859    0.33084   0.389    0.698    
## category_code_LT01_15_count -0.27871    0.76748  -0.363    0.717    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6165 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.616449404700036 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0257 -0.7941  0.0069  0.8966  3.4468 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.946397   0.088602 112.259  < 2e-16 ***
## category_code_LT01_1_count   0.444782   0.084461   5.266 2.09e-07 ***
## category_code_LT01_2_count   0.839802   0.073194  11.474  < 2e-16 ***
## category_code_LT01_5_count   1.001800   0.061923  16.178  < 2e-16 ***
## category_code_LT01_12_count -0.006229   0.209730  -0.030    0.976    
## category_code_LT01_14_count  0.134911   0.331321   0.407    0.684    
## category_code_LT01_16_count  0.385339   1.181079   0.326    0.744    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.616418476192768 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0252 -0.7982  0.0169  0.8845  3.4494 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.943726   0.088498 112.361  < 2e-16 ***
## category_code_LT01_1_count   0.455142   0.085375   5.331 1.49e-07 ***
## category_code_LT01_2_count   0.845617   0.072933  11.594  < 2e-16 ***
## category_code_LT01_5_count   1.004935   0.061467  16.349  < 2e-16 ***
## category_code_LT01_12_count -0.004258   0.209546  -0.020    0.984    
## category_code_LT01_15_count -0.272802   0.767916  -0.355    0.723    
## category_code_LT01_16_count  0.346138   1.180038   0.293    0.769    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616477287853673 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0247 -0.7932  0.0197  0.8874  3.4477 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94548    0.08862 112.221  < 2e-16 ***
## category_code_LT01_1_count   0.44778    0.08663   5.169 3.43e-07 ***
## category_code_LT01_2_count   0.84400    0.07152  11.802  < 2e-16 ***
## category_code_LT01_5_count   1.00177    0.06164  16.253  < 2e-16 ***
## category_code_LT01_13_count  0.02793    0.24830   0.112    0.910    
## category_code_LT01_14_count  0.12811    0.33024   0.388    0.698    
## category_code_LT01_15_count -0.26930    0.76990  -0.350    0.727    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6165 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.616467972552182 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0254 -0.7938  0.0071  0.8992  3.4466 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94657    0.08861 112.255  < 2e-16 ***
## category_code_LT01_1_count   0.44230    0.08486   5.212 2.75e-07 ***
## category_code_LT01_2_count   0.83844    0.07205  11.637  < 2e-16 ***
## category_code_LT01_5_count   1.00117    0.06166  16.237  < 2e-16 ***
## category_code_LT01_13_count  0.03886    0.24747   0.157    0.875    
## category_code_LT01_14_count  0.13509    0.33073   0.408    0.683    
## category_code_LT01_16_count  0.39272    1.18182   0.332    0.740    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6165 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.616429211584869 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0250 -0.7966  0.0146  0.8872  3.4493 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94388    0.08850 112.356  < 2e-16 ***
## category_code_LT01_1_count   0.45309    0.08580   5.281 1.94e-07 ***
## category_code_LT01_2_count   0.84455    0.07165  11.788  < 2e-16 ***
## category_code_LT01_5_count   1.00448    0.06114  16.428  < 2e-16 ***
## category_code_LT01_13_count  0.02956    0.24849   0.119    0.905    
## category_code_LT01_15_count -0.26375    0.77039  -0.342    0.732    
## category_code_LT01_16_count  0.35212    1.18082   0.298    0.766    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.616545042560932 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0248 -0.7932  0.0175  0.8918  3.4475 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94569    0.08861 112.235  < 2e-16 ***
## category_code_LT01_1_count   0.45013    0.08527   5.279 1.96e-07 ***
## category_code_LT01_2_count   0.84138    0.07202  11.683  < 2e-16 ***
## category_code_LT01_5_count   1.00160    0.06159  16.263  < 2e-16 ***
## category_code_LT01_14_count  0.13329    0.33067   0.403    0.687    
## category_code_LT01_15_count -0.26940    0.76709  -0.351    0.726    
## category_code_LT01_16_count  0.37251    1.18146   0.315    0.753    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6165 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 0.635903488524998 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9669 -0.7422  0.0710  0.8519  3.4843 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95260    0.08614 115.533  < 2e-16 ***
## category_code_LT01_1_count  0.22942    0.08814   2.603  0.00953 ** 
## category_code_LT01_3_count  0.29197    0.11189   2.609  0.00934 ** 
## category_code_LT01_4_count  0.65694    0.09542   6.885 1.78e-11 ***
## category_code_LT01_5_count  0.90811    0.06140  14.789  < 2e-16 ***
## category_code_LT01_6_count  0.41904    0.14835   2.825  0.00493 ** 
## category_code_LT01_7_count  0.45732    0.15140   3.021  0.00265 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6403, Adjusted R-squared:  0.6359 
## F-statistic: 145.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 0.629549056205586 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9792 -0.7418  0.0440  0.8987  3.4647 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95224    0.08692 114.502  < 2e-16 ***
## category_code_LT01_1_count  0.25492    0.08859   2.878  0.00418 ** 
## category_code_LT01_3_count  0.30730    0.11277   2.725  0.00666 ** 
## category_code_LT01_4_count  0.73724    0.09236   7.982 1.03e-14 ***
## category_code_LT01_5_count  0.92631    0.06249  14.824  < 2e-16 ***
## category_code_LT01_6_count  0.42582    0.14973   2.844  0.00464 ** 
## category_code_LT01_8_count -0.20059    0.27164  -0.738  0.46061    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.634,  Adjusted R-squared:  0.6295 
## F-statistic: 141.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 0.631221710101217 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9648 -0.7587  0.0470  0.9201  3.4845 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94735    0.08672 114.710  < 2e-16 ***
## category_code_LT01_1_count  0.24819    0.08841   2.807  0.00519 ** 
## category_code_LT01_3_count  0.27834    0.11374   2.447  0.01475 *  
## category_code_LT01_4_count  0.72679    0.09239   7.866 2.35e-14 ***
## category_code_LT01_5_count  0.91267    0.06182  14.764  < 2e-16 ***
## category_code_LT01_6_count  0.40884    0.14951   2.735  0.00647 ** 
## category_code_LT01_9_count  0.37334    0.22413   1.666  0.09640 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6357, Adjusted R-squared:  0.6312 
## F-statistic: 142.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 0.629461169840905 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9578 -0.7577  0.0588  0.8991  3.4065 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93510    0.09008 110.287  < 2e-16 ***
## category_code_LT01_1_count   0.25593    0.08867   2.887  0.00407 ** 
## category_code_LT01_3_count   0.29309    0.11453   2.559  0.01079 *  
## category_code_LT01_4_count   0.73671    0.09239   7.974 1.09e-14 ***
## category_code_LT01_5_count   0.92022    0.06183  14.882  < 2e-16 ***
## category_code_LT01_6_count   0.40666    0.15147   2.685  0.00751 ** 
## category_code_LT01_10_count  0.07464    0.11400   0.655  0.51294    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6339, Adjusted R-squared:  0.6295 
## F-statistic: 141.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 0.634463460827613 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9794 -0.7501  0.0706  0.9020  3.4691 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96054    0.08639 115.295  < 2e-16 ***
## category_code_LT01_1_count   0.21722    0.08899   2.441  0.01500 *  
## category_code_LT01_3_count   0.23545    0.11509   2.046  0.04131 *  
## category_code_LT01_4_count   0.63731    0.09918   6.426  3.1e-10 ***
## category_code_LT01_5_count   0.91468    0.06143  14.889  < 2e-16 ***
## category_code_LT01_6_count   0.35876    0.15051   2.384  0.01752 *  
## category_code_LT01_11_count  0.30656    0.11462   2.675  0.00773 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.362 on 491 degrees of freedom
## Multiple R-squared:  0.6389, Adjusted R-squared:  0.6345 
## F-statistic: 144.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 0.629138789645216 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9728 -0.7402  0.0603  0.9014  3.4739 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.950659   0.086940 114.455  < 2e-16 ***
## category_code_LT01_1_count  0.252791   0.089165   2.835  0.00477 ** 
## category_code_LT01_3_count  0.305924   0.113004   2.707  0.00702 ** 
## category_code_LT01_4_count  0.737842   0.092628   7.966 1.15e-14 ***
## category_code_LT01_5_count  0.919353   0.062103  14.804  < 2e-16 ***
## category_code_LT01_6_count  0.421311   0.150691   2.796  0.00538 ** 
## category_code_LT01_12_count 0.007957   0.205858   0.039  0.96918    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.372 on 491 degrees of freedom
## Multiple R-squared:  0.6336, Adjusted R-squared:  0.6291 
## F-statistic: 141.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 0.629155812014575 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9728 -0.7403  0.0632  0.9015  3.4739 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95075    0.08694 114.456  < 2e-16 ***
## category_code_LT01_1_count   0.25124    0.08948   2.808  0.00519 ** 
## category_code_LT01_3_count   0.30611    0.11282   2.713  0.00690 ** 
## category_code_LT01_4_count   0.73703    0.09266   7.955 1.25e-14 ***
## category_code_LT01_5_count   0.91920    0.06190  14.851  < 2e-16 ***
## category_code_LT01_6_count   0.42248    0.14976   2.821  0.00498 ** 
## category_code_LT01_13_count  0.03771    0.24328   0.155  0.87687    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.372 on 491 degrees of freedom
## Multiple R-squared:  0.6336, Adjusted R-squared:  0.6292 
## F-statistic: 141.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 0.629340848787112 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9721 -0.7422  0.0660  0.9009  3.4761 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95265    0.08700 114.397  < 2e-16 ***
## category_code_LT01_1_count   0.24786    0.08917   2.780  0.00565 ** 
## category_code_LT01_3_count   0.30878    0.11291   2.735  0.00647 ** 
## category_code_LT01_4_count   0.72934    0.09391   7.767 4.74e-14 ***
## category_code_LT01_5_count   0.91554    0.06232  14.690  < 2e-16 ***
## category_code_LT01_6_count   0.42912    0.15032   2.855  0.00449 ** 
## category_code_LT01_14_count  0.16998    0.32764   0.519  0.60413    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6338, Adjusted R-squared:  0.6293 
## F-statistic: 141.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 0.629407703806436 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9712 -0.7484  0.0615  0.9030  3.4756 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94932    0.08694 114.444  < 2e-16 ***
## category_code_LT01_1_count   0.26175    0.08972   2.917  0.00369 ** 
## category_code_LT01_3_count   0.31338    0.11343   2.763  0.00595 ** 
## category_code_LT01_4_count   0.73757    0.09238   7.984 1.01e-14 ***
## category_code_LT01_5_count   0.91898    0.06184  14.861  < 2e-16 ***
## category_code_LT01_6_count   0.42448    0.14973   2.835  0.00477 ** 
## category_code_LT01_15_count -0.45328    0.75781  -0.598  0.55002    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6339, Adjusted R-squared:  0.6294 
## F-statistic: 141.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 0.629860476790333 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9718 -0.7402  0.0426  0.9034  3.4754 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95064    0.08685 114.567  < 2e-16 ***
## category_code_LT01_1_count   0.25539    0.08855   2.884  0.00410 ** 
## category_code_LT01_3_count   0.29100    0.11377   2.558  0.01084 *  
## category_code_LT01_4_count   0.73638    0.09233   7.975 1.08e-14 ***
## category_code_LT01_5_count   0.91803    0.06181  14.852  < 2e-16 ***
## category_code_LT01_6_count   0.43297    0.15000   2.886  0.00407 ** 
## category_code_LT01_16_count  1.13888    1.16307   0.979  0.32796    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6343, Adjusted R-squared:  0.6299 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 0.630384887468357 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0012 -0.7584  0.0442  0.8470  3.4394 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96880    0.08667 115.016  < 2e-16 ***
## category_code_LT01_1_count  0.24964    0.08860   2.818  0.00503 ** 
## category_code_LT01_3_count  0.32721    0.11210   2.919  0.00367 ** 
## category_code_LT01_4_count  0.72916    0.09256   7.878 2.16e-14 ***
## category_code_LT01_5_count  0.93423    0.06217  15.027  < 2e-16 ***
## category_code_LT01_7_count  0.46328    0.15260   3.036  0.00253 ** 
## category_code_LT01_8_count -0.19715    0.27128  -0.727  0.46773    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6348, Adjusted R-squared:  0.6304 
## F-statistic: 142.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 0.631719271763418 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9870 -0.7312  0.0163  0.8775  3.4589 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96356    0.08652 115.165  < 2e-16 ***
## category_code_LT01_1_count  0.24404    0.08844   2.759  0.00601 ** 
## category_code_LT01_3_count  0.30019    0.11315   2.653  0.00824 ** 
## category_code_LT01_4_count  0.72159    0.09254   7.797 3.82e-14 ***
## category_code_LT01_5_count  0.92123    0.06151  14.978  < 2e-16 ***
## category_code_LT01_7_count  0.43691    0.15303   2.855  0.00449 ** 
## category_code_LT01_9_count  0.34158    0.22479   1.520  0.12926    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6362, Adjusted R-squared:  0.6317 
## F-statistic: 143.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 0.630516559844338 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9746 -0.7362  0.0307  0.8680  3.3792 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94667    0.08998 110.540  < 2e-16 ***
## category_code_LT01_1_count   0.25111    0.08863   2.833  0.00480 ** 
## category_code_LT01_3_count   0.30807    0.11406   2.701  0.00715 ** 
## category_code_LT01_4_count   0.72662    0.09262   7.846 2.71e-14 ***
## category_code_LT01_5_count   0.92771    0.06147  15.093  < 2e-16 ***
## category_code_LT01_7_count   0.44957    0.15303   2.938  0.00346 ** 
## category_code_LT01_10_count  0.09464    0.11285   0.839  0.40208    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.635,  Adjusted R-squared:  0.6305 
## F-statistic: 142.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 0.63435952358078 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9982 -0.7553  0.0581  0.8637  3.4471 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97383    0.08622 115.680  < 2e-16 ***
## category_code_LT01_1_count   0.21696    0.08901   2.438   0.0151 *  
## category_code_LT01_3_count   0.25883    0.11486   2.253   0.0247 *  
## category_code_LT01_4_count   0.64313    0.09877   6.511 1.84e-10 ***
## category_code_LT01_5_count   0.92263    0.06118  15.081  < 2e-16 ***
## category_code_LT01_7_count   0.36813    0.15640   2.354   0.0190 *  
## category_code_LT01_11_count  0.28277    0.11670   2.423   0.0158 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.362 on 491 degrees of freedom
## Multiple R-squared:  0.6388, Adjusted R-squared:  0.6344 
## F-statistic: 144.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 0.63007942342419 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9933 -0.7497  0.0389  0.8655  3.4510 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96700    0.08668 114.990  < 2e-16 ***
## category_code_LT01_1_count   0.24420    0.08924   2.737  0.00643 ** 
## category_code_LT01_3_count   0.32321    0.11239   2.876  0.00421 ** 
## category_code_LT01_4_count   0.72665    0.09305   7.809 3.51e-14 ***
## category_code_LT01_5_count   0.92530    0.06183  14.966  < 2e-16 ***
## category_code_LT01_7_count   0.45997    0.15260   3.014  0.00271 ** 
## category_code_LT01_12_count  0.07143    0.20428   0.350  0.72673    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:  0.6301 
## F-statistic: 142.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 0.630028245431468 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9950 -0.7492  0.0245  0.8585  3.4482 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96691    0.08669 114.977  < 2e-16 ***
## category_code_LT01_1_count   0.25062    0.08936   2.805  0.00524 ** 
## category_code_LT01_3_count   0.32579    0.11214   2.905  0.00383 ** 
## category_code_LT01_4_count   0.73067    0.09265   7.886 2.04e-14 ***
## category_code_LT01_5_count   0.92793    0.06153  15.080  < 2e-16 ***
## category_code_LT01_7_count   0.46397    0.15350   3.022  0.00264 ** 
## category_code_LT01_13_count -0.05696    0.24435  -0.233  0.81578    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:   0.63 
## F-statistic: 142.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 0.629990628288333 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9948 -0.7499  0.0272  0.8603  3.4487 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96737    0.08679 114.840  < 2e-16 ***
## category_code_LT01_1_count   0.24732    0.08908   2.776  0.00571 ** 
## category_code_LT01_3_count   0.32632    0.11233   2.905  0.00384 ** 
## category_code_LT01_4_count   0.72905    0.09346   7.800 3.73e-14 ***
## category_code_LT01_5_count   0.92705    0.06189  14.978  < 2e-16 ***
## category_code_LT01_7_count   0.45947    0.15293   3.004  0.00280 ** 
## category_code_LT01_14_count  0.02170    0.32664   0.066  0.94706    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:   0.63 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 0.630093245855235 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9939 -0.7439  0.0457  0.8606  3.4495 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96630    0.08670 114.950  < 2e-16 ***
## category_code_LT01_1_count   0.25351    0.08984   2.822  0.00497 ** 
## category_code_LT01_3_count   0.33062    0.11284   2.930  0.00355 ** 
## category_code_LT01_4_count   0.73033    0.09259   7.887 2.02e-14 ***
## category_code_LT01_5_count   0.92728    0.06151  15.076  < 2e-16 ***
## category_code_LT01_7_count   0.45737    0.15278   2.994  0.00290 ** 
## category_code_LT01_15_count -0.28413    0.75768  -0.375  0.70782    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6346, Adjusted R-squared:  0.6301 
## F-statistic: 142.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 0.63043093647932 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9946 -0.7506  0.0304  0.8614  3.4491 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96738    0.08664 115.048  < 2e-16 ***
## category_code_LT01_1_count   0.25003    0.08860   2.822  0.00497 ** 
## category_code_LT01_3_count   0.31474    0.11301   2.785  0.00556 ** 
## category_code_LT01_4_count   0.73005    0.09255   7.889    2e-14 ***
## category_code_LT01_5_count   0.92670    0.06148  15.072  < 2e-16 ***
## category_code_LT01_7_count   0.46019    0.15253   3.017  0.00269 ** 
## category_code_LT01_16_count  0.88973    1.15892   0.768  0.44302    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6349, Adjusted R-squared:  0.6304 
## F-statistic: 142.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 0.625968577685659 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9974 -0.7549  0.0347  0.8840  3.4419 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96273    0.08721 114.233  < 2e-16 ***
## category_code_LT01_1_count  0.26764    0.08883   3.013  0.00272 ** 
## category_code_LT01_3_count  0.31002    0.11400   2.719  0.00677 ** 
## category_code_LT01_4_count  0.79695    0.08936   8.919  < 2e-16 ***
## category_code_LT01_5_count  0.93743    0.06258  14.980  < 2e-16 ***
## category_code_LT01_8_count -0.18847    0.27291  -0.691  0.49015    
## category_code_LT01_9_count  0.41028    0.22551   1.819  0.06946 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 0.624352831336426 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9803 -0.7749  0.0435  0.8656  3.3202 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94020    0.09071 109.581  < 2e-16 ***
## category_code_LT01_1_count   0.27711    0.08902   3.113  0.00196 ** 
## category_code_LT01_3_count   0.31803    0.11498   2.766  0.00589 ** 
## category_code_LT01_4_count   0.80518    0.08938   9.008  < 2e-16 ***
## category_code_LT01_5_count   0.94529    0.06257  15.108  < 2e-16 ***
## category_code_LT01_8_count  -0.17980    0.27343  -0.658  0.51113    
## category_code_LT01_10_count  0.12342    0.11343   1.088  0.27707    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6289, Adjusted R-squared:  0.6244 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 0.630456299325513 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0085 -0.7648  0.0495  0.8665  3.4317 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97523    0.08671 115.045  < 2e-16 ***
## category_code_LT01_1_count   0.22942    0.08941   2.566   0.0106 *  
## category_code_LT01_3_count   0.25550    0.11549   2.212   0.0274 *  
## category_code_LT01_4_count   0.68513    0.09771   7.012 7.84e-12 ***
## category_code_LT01_5_count   0.93540    0.06214  15.053  < 2e-16 ***
## category_code_LT01_8_count  -0.14754    0.27128  -0.544   0.5868    
## category_code_LT01_11_count  0.34750    0.11387   3.052   0.0024 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6349, Adjusted R-squared:  0.6305 
## F-statistic: 142.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 0.623554880665425 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0051 -0.7624  0.0190  0.8616  3.4320 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96666    0.08747 113.947  < 2e-16 ***
## category_code_LT01_1_count   0.26961    0.08969   3.006  0.00278 ** 
## category_code_LT01_3_count   0.33878    0.11329   2.990  0.00293 ** 
## category_code_LT01_4_count   0.80837    0.08976   9.006  < 2e-16 ***
## category_code_LT01_5_count   0.94289    0.06293  14.983  < 2e-16 ***
## category_code_LT01_8_count  -0.17697    0.27381  -0.646  0.51836    
## category_code_LT01_12_count  0.07735    0.20618   0.375  0.70770    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6236 
## F-statistic: 138.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 0.623449039940587 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0067 -0.7663  0.0244  0.8376  3.4296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96675    0.08748 113.929  < 2e-16 ***
## category_code_LT01_1_count   0.27296    0.08996   3.034  0.00254 ** 
## category_code_LT01_3_count   0.34165    0.11304   3.022  0.00264 ** 
## category_code_LT01_4_count   0.81158    0.08950   9.068  < 2e-16 ***
## category_code_LT01_5_count   0.94502    0.06271  15.070  < 2e-16 ***
## category_code_LT01_8_count  -0.17279    0.27425  -0.630  0.52894    
## category_code_LT01_13_count  0.01277    0.24557   0.052  0.95856    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.628,  Adjusted R-squared:  0.6234 
## F-statistic: 138.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 0.623500378183179 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0066 -0.7632  0.0315  0.8556  3.4303 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96788    0.08758 113.809  < 2e-16 ***
## category_code_LT01_1_count   0.27107    0.08958   3.026  0.00261 ** 
## category_code_LT01_3_count   0.34330    0.11320   3.033  0.00255 ** 
## category_code_LT01_4_count   0.80808    0.09044   8.935  < 2e-16 ***
## category_code_LT01_5_count   0.94331    0.06303  14.965  < 2e-16 ***
## category_code_LT01_8_count  -0.17459    0.27371  -0.638  0.52386    
## category_code_LT01_14_count  0.08679    0.32884   0.264  0.79195    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.628,  Adjusted R-squared:  0.6235 
## F-statistic: 138.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 0.62364814859698 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0054 -0.7702  0.0277  0.8405  3.4310 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96564    0.08748 113.916  < 2e-16 ***
## category_code_LT01_1_count   0.28111    0.09023   3.115  0.00195 ** 
## category_code_LT01_3_count   0.34805    0.11370   3.061  0.00233 ** 
## category_code_LT01_4_count   0.81183    0.08925   9.096  < 2e-16 ***
## category_code_LT01_5_count   0.94474    0.06263  15.084  < 2e-16 ***
## category_code_LT01_8_count  -0.17314    0.27363  -0.633  0.52721    
## category_code_LT01_15_count -0.39109    0.76338  -0.512  0.60866    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6236 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 0.62392628719247 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0068 -0.7625  0.0167  0.8388  3.4296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96711    0.08743 114.006  < 2e-16 ***
## category_code_LT01_1_count   0.27592    0.08906   3.098  0.00206 ** 
## category_code_LT01_3_count   0.33013    0.11391   2.898  0.00392 ** 
## category_code_LT01_4_count   0.81208    0.08922   9.102  < 2e-16 ***
## category_code_LT01_5_count   0.94469    0.06261  15.089  < 2e-16 ***
## category_code_LT01_8_count  -0.18425    0.27386  -0.673  0.50138    
## category_code_LT01_16_count  0.92592    1.17046   0.791  0.42928    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.6239 
## F-statistic: 138.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 0.626212282951528 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9700 -0.7442  0.0197  0.9112  3.3602 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93949    0.09047 109.868  < 2e-16 ***
## category_code_LT01_1_count   0.26905    0.08883   3.029  0.00259 ** 
## category_code_LT01_3_count   0.29118    0.11569   2.517  0.01216 *  
## category_code_LT01_4_count   0.79253    0.08949   8.856  < 2e-16 ***
## category_code_LT01_5_count   0.93138    0.06187  15.054  < 2e-16 ***
## category_code_LT01_9_count   0.38434    0.22659   1.696  0.09048 .  
## category_code_LT01_10_count  0.10158    0.11375   0.893  0.37232    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6307, Adjusted R-squared:  0.6262 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 0.632242773700026 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9948 -0.7521  0.0562  0.8728  3.4503 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97006    0.08650 115.258  < 2e-16 ***
## category_code_LT01_1_count   0.22367    0.08918   2.508  0.01246 *  
## category_code_LT01_3_count   0.22827    0.11624   1.964  0.05012 .  
## category_code_LT01_4_count   0.67515    0.09764   6.915 1.47e-11 ***
## category_code_LT01_5_count   0.92317    0.06142  15.030  < 2e-16 ***
## category_code_LT01_9_count   0.36669    0.22389   1.638  0.10210    
## category_code_LT01_11_count  0.33857    0.11373   2.977  0.00306 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.366 on 491 degrees of freedom
## Multiple R-squared:  0.6367, Adjusted R-squared:  0.6322 
## F-statistic: 143.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 0.625695596240473 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9898 -0.7506  0.0353  0.9059  3.4530 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96107    0.08722 114.211  < 2e-16 ***
## category_code_LT01_1_count   0.26222    0.08947   2.931  0.00354 ** 
## category_code_LT01_3_count   0.30640    0.11429   2.681  0.00759 ** 
## category_code_LT01_4_count   0.79406    0.08988   8.835  < 2e-16 ***
## category_code_LT01_5_count   0.92884    0.06223  14.925  < 2e-16 ***
## category_code_LT01_9_count   0.40515    0.22549   1.797  0.07299 .  
## category_code_LT01_12_count  0.07073    0.20549   0.344  0.73083    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6257 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 0.625639778014328 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9911 -0.7508  0.0425  0.8938  3.4510 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96129    0.08723 114.202  < 2e-16 ***
## category_code_LT01_1_count   0.26321    0.08973   2.933  0.00351 ** 
## category_code_LT01_3_count   0.30875    0.11405   2.707  0.00702 ** 
## category_code_LT01_4_count   0.79582    0.08966   8.876  < 2e-16 ***
## category_code_LT01_5_count   0.93049    0.06197  15.016  < 2e-16 ***
## category_code_LT01_9_count   0.40886    0.22601   1.809  0.07106 .  
## category_code_LT01_13_count  0.05210    0.24492   0.213  0.83162    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6256 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 0.62561743470361 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9913 -0.7513  0.0440  0.8951  3.4509 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96172    0.08734 114.053  < 2e-16 ***
## category_code_LT01_1_count   0.26472    0.08933   2.963  0.00319 ** 
## category_code_LT01_3_count   0.30996    0.11429   2.712  0.00692 ** 
## category_code_LT01_4_count   0.79552    0.09047   8.793  < 2e-16 ***
## category_code_LT01_5_count   0.93016    0.06229  14.932  < 2e-16 ***
## category_code_LT01_9_count   0.40357    0.22611   1.785  0.07490 .  
## category_code_LT01_14_count  0.04152    0.32876   0.126  0.89955    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6256 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 0.625751689650218 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9903 -0.7498  0.0565  0.8912  3.4517 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96028    0.08723 114.181  < 2e-16 ***
## category_code_LT01_1_count   0.27237    0.09004   3.025  0.00262 ** 
## category_code_LT01_3_count   0.31481    0.11479   2.743  0.00632 ** 
## category_code_LT01_4_count   0.79737    0.08938   8.921  < 2e-16 ***
## category_code_LT01_5_count   0.93076    0.06191  15.034  < 2e-16 ***
## category_code_LT01_9_count   0.40134    0.22569   1.778  0.07597 .  
## category_code_LT01_15_count -0.33396    0.76196  -0.438  0.66137    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6258 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 0.625988958811919 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9912 -0.7510  0.0312  0.9060  3.4510 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96147    0.08718 114.259  < 2e-16 ***
## category_code_LT01_1_count   0.26794    0.08884   3.016  0.00269 ** 
## category_code_LT01_3_count   0.29900    0.11486   2.603  0.00952 ** 
## category_code_LT01_4_count   0.79761    0.08935   8.926  < 2e-16 ***
## category_code_LT01_5_count   0.93036    0.06189  15.032  < 2e-16 ***
## category_code_LT01_9_count   0.40104    0.22549   1.778  0.07594 .  
## category_code_LT01_16_count  0.82778    1.16634   0.710  0.47821    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 0.63098053204451 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9795 -0.7462  0.0451  0.8825  3.3396 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94980    0.08996 110.604  < 2e-16 ***
## category_code_LT01_1_count   0.23129    0.08937   2.588  0.00994 ** 
## category_code_LT01_3_count   0.23325    0.11723   1.990  0.04718 *  
## category_code_LT01_4_count   0.67962    0.09776   6.952 1.15e-11 ***
## category_code_LT01_5_count   0.93026    0.06138  15.157  < 2e-16 ***
## category_code_LT01_10_count  0.11209    0.11244   0.997  0.31932    
## category_code_LT01_11_count  0.34621    0.11378   3.043  0.00247 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6354, Adjusted R-squared:  0.631 
## F-statistic: 142.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 0.624096047467934 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9736 -0.7664  0.0101  0.8876  3.3335 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93922    0.09073 109.552  < 2e-16 ***
## category_code_LT01_1_count   0.27196    0.08967   3.033  0.00255 ** 
## category_code_LT01_3_count   0.31490    0.11521   2.733  0.00650 ** 
## category_code_LT01_4_count   0.80257    0.08988   8.929  < 2e-16 ***
## category_code_LT01_5_count   0.93710    0.06220  15.065  < 2e-16 ***
## category_code_LT01_10_count  0.12044    0.11354   1.061  0.28932    
## category_code_LT01_12_count  0.06409    0.20610   0.311  0.75597    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6241 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 0.624024405039944 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9748 -0.7672  0.0064  0.8715  3.3302 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93907    0.09075 109.526  < 2e-16 ***
## category_code_LT01_1_count   0.27465    0.08990   3.055  0.00237 ** 
## category_code_LT01_3_count   0.31706    0.11502   2.757  0.00606 ** 
## category_code_LT01_4_count   0.80508    0.08963   8.982  < 2e-16 ***
## category_code_LT01_5_count   0.93896    0.06192  15.164  < 2e-16 ***
## category_code_LT01_10_count  0.12168    0.11352   1.072  0.28429    
## category_code_LT01_13_count  0.01367    0.24503   0.056  0.95555    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.624 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 0.624022068393146 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9748 -0.7686  0.0063  0.8804  3.3302 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.939059   0.091313 108.846  < 2e-16 ***
## category_code_LT01_1_count  0.275267   0.089656   3.070  0.00226 ** 
## category_code_LT01_3_count  0.317115   0.115593   2.743  0.00630 ** 
## category_code_LT01_4_count  0.805317   0.090425   8.906  < 2e-16 ***
## category_code_LT01_5_count  0.939029   0.062315  15.069  < 2e-16 ***
## category_code_LT01_10_count 0.121683   0.116619   1.043  0.29727    
## category_code_LT01_14_count 0.002597   0.337764   0.008  0.99387    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.624 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 0.624287730365187 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9722 -0.7638  0.0329  0.8742  3.3277 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93677    0.09078 109.463  < 2e-16 ***
## category_code_LT01_1_count   0.28411    0.09022   3.149  0.00174 ** 
## category_code_LT01_3_count   0.32352    0.11550   2.801  0.00530 ** 
## category_code_LT01_4_count   0.80509    0.08939   9.006  < 2e-16 ***
## category_code_LT01_5_count   0.93861    0.06187  15.172  < 2e-16 ***
## category_code_LT01_10_count  0.12642    0.11367   1.112  0.26662    
## category_code_LT01_15_count -0.45048    0.76447  -0.589  0.55595    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6288, Adjusted R-squared:  0.6243 
## F-statistic: 138.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 0.624430792376867 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9750 -0.7637  0.0077  0.8831  3.3325 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93974    0.09069 109.603  < 2e-16 ***
## category_code_LT01_1_count   0.27732    0.08901   3.116  0.00194 ** 
## category_code_LT01_3_count   0.30674    0.11581   2.649  0.00834 ** 
## category_code_LT01_4_count   0.80571    0.08938   9.015  < 2e-16 ***
## category_code_LT01_5_count   0.93831    0.06186  15.169  < 2e-16 ***
## category_code_LT01_10_count  0.11966    0.11343   1.055  0.29198    
## category_code_LT01_16_count  0.85436    1.16871   0.731  0.46511    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6244 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 0.630361268473329 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0057 -0.7640  0.0384  0.8507  3.4355 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97441    0.08669 115.052  < 2e-16 ***
## category_code_LT01_1_count   0.23078    0.08967   2.574  0.01036 *  
## category_code_LT01_3_count   0.25426    0.11547   2.202  0.02813 *  
## category_code_LT01_4_count   0.68415    0.09773   7.001 8.41e-12 ***
## category_code_LT01_5_count   0.93264    0.06170  15.116  < 2e-16 ***
## category_code_LT01_11_count  0.36138    0.11745   3.077  0.00221 ** 
## category_code_LT01_12_count -0.08674    0.21070  -0.412  0.68075    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6348, Adjusted R-squared:  0.6304 
## F-statistic: 142.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 0.63023383375046 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0037 -0.7636  0.0431  0.8732  3.4385 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.974003   0.086707 115.031  < 2e-16 ***
## category_code_LT01_1_count   0.227931   0.090173   2.528  0.01179 *  
## category_code_LT01_3_count   0.253939   0.115494   2.199  0.02836 *  
## category_code_LT01_4_count   0.684607   0.097855   6.996 8.66e-12 ***
## category_code_LT01_5_count   0.930289   0.061474  15.133  < 2e-16 ***
## category_code_LT01_11_count  0.349512   0.113916   3.068  0.00227 ** 
## category_code_LT01_13_count -0.003477   0.243012  -0.014  0.98859    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6347, Adjusted R-squared:  0.6302 
## F-statistic: 142.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 0.630261034312342 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0036 -0.7644  0.0445  0.8742  3.4392 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97482    0.08681 114.910  < 2e-16 ***
## category_code_LT01_1_count   0.22599    0.08987   2.515   0.0122 *  
## category_code_LT01_3_count   0.25523    0.11568   2.206   0.0278 *  
## category_code_LT01_4_count   0.68197    0.09866   6.913 1.49e-11 ***
## category_code_LT01_5_count   0.92892    0.06184  15.022  < 2e-16 ***
## category_code_LT01_11_count  0.34898    0.11387   3.065   0.0023 ** 
## category_code_LT01_14_count  0.06212    0.32593   0.191   0.8489    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6347, Adjusted R-squared:  0.6303 
## F-statistic: 142.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 0.630454646031431 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0023 -0.7625  0.0452  0.8654  3.4401 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97290    0.08670 115.024  < 2e-16 ***
## category_code_LT01_1_count   0.23556    0.09051   2.602  0.00954 ** 
## category_code_LT01_3_count   0.26054    0.11610   2.244  0.02526 *  
## category_code_LT01_4_count   0.68430    0.09771   7.003 8.26e-12 ***
## category_code_LT01_5_count   0.92982    0.06142  15.138  < 2e-16 ***
## category_code_LT01_11_count  0.34990    0.11382   3.074  0.00223 ** 
## category_code_LT01_15_count -0.40988    0.75646  -0.542  0.58818    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6349, Adjusted R-squared:  0.6305 
## F-statistic: 142.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 0.630628239705316 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0034 -0.7638  0.0443  0.8711  3.4391 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97426    0.08666 115.099  < 2e-16 ***
## category_code_LT01_1_count   0.22990    0.08939   2.572  0.01041 *  
## category_code_LT01_3_count   0.24371    0.11629   2.096  0.03662 *  
## category_code_LT01_4_count   0.68511    0.09769   7.013 7.75e-12 ***
## category_code_LT01_5_count   0.92953    0.06141  15.136  < 2e-16 ***
## category_code_LT01_11_count  0.34833    0.11380   3.061  0.00233 ** 
## category_code_LT01_16_count  0.83915    1.15871   0.724  0.46928    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6351, Adjusted R-squared:  0.6306 
## F-statistic: 142.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 0.623240489006466 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9994 -0.7548  0.0176  0.8502  3.4402 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96521    0.08748 113.919  < 2e-16 ***
## category_code_LT01_1_count   0.26706    0.09055   2.949  0.00333 ** 
## category_code_LT01_3_count   0.33766    0.11332   2.980  0.00303 ** 
## category_code_LT01_4_count   0.80817    0.09001   8.979  < 2e-16 ***
## category_code_LT01_5_count   0.93673    0.06231  15.033  < 2e-16 ***
## category_code_LT01_12_count  0.07288    0.20617   0.354  0.72385    
## category_code_LT01_13_count  0.02148    0.24517   0.088  0.93021    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6278, Adjusted R-squared:  0.6232 
## F-statistic:   138 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 0.623276065600209 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9994 -0.7557 -0.0053  0.8652  3.4408 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96616    0.08758 113.797  < 2e-16 ***
## category_code_LT01_1_count   0.26606    0.09014   2.952  0.00331 ** 
## category_code_LT01_3_count   0.33922    0.11352   2.988  0.00295 ** 
## category_code_LT01_4_count   0.80548    0.09086   8.865  < 2e-16 ***
## category_code_LT01_5_count   0.93535    0.06264  14.933  < 2e-16 ***
## category_code_LT01_12_count  0.06985    0.20662   0.338  0.73547    
## category_code_LT01_14_count  0.07664    0.32967   0.232  0.81626    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6278, Adjusted R-squared:  0.6233 
## F-statistic:   138 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 0.623425823474816 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9982 -0.7554  0.0331  0.8613  3.4414 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96410    0.08748 113.907  < 2e-16 ***
## category_code_LT01_1_count   0.27570    0.09094   3.031  0.00256 ** 
## category_code_LT01_3_count   0.34408    0.11402   3.018  0.00268 ** 
## category_code_LT01_4_count   0.80885    0.08978   9.010  < 2e-16 ***
## category_code_LT01_5_count   0.93666    0.06226  15.044  < 2e-16 ***
## category_code_LT01_12_count  0.06850    0.20631   0.332  0.74003    
## category_code_LT01_15_count -0.38167    0.76436  -0.499  0.61777    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.628,  Adjusted R-squared:  0.6234 
## F-statistic: 138.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 0.623678315381507 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9991 -0.7550  0.0010  0.8764  3.4407 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96543    0.08742 113.991  < 2e-16 ***
## category_code_LT01_1_count   0.27022    0.08969   3.013  0.00272 ** 
## category_code_LT01_3_count   0.32648    0.11421   2.859  0.00444 ** 
## category_code_LT01_4_count   0.80885    0.08975   9.013  < 2e-16 ***
## category_code_LT01_5_count   0.93608    0.06225  15.038  < 2e-16 ***
## category_code_LT01_12_count  0.07396    0.20604   0.359  0.71979    
## category_code_LT01_16_count  0.88983    1.16947   0.761  0.44710    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6237 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 0.623195414765725 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0009 -0.7560  0.0253  0.8479  3.4386 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96642    0.08759 113.784  < 2e-16 ***
## category_code_LT01_1_count   0.26827    0.09047   2.965  0.00317 ** 
## category_code_LT01_3_count   0.34199    0.11323   3.020  0.00266 ** 
## category_code_LT01_4_count   0.80772    0.09071   8.904  < 2e-16 ***
## category_code_LT01_5_count   0.93712    0.06241  15.016  < 2e-16 ***
## category_code_LT01_13_count  0.02347    0.24520   0.096  0.92379    
## category_code_LT01_14_count  0.08466    0.32899   0.257  0.79702    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6277, Adjusted R-squared:  0.6232 
## F-statistic:   138 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 0.623342892041582 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9997 -0.7567  0.0259  0.8480  3.4391 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96419    0.08749 113.888  < 2e-16 ***
## category_code_LT01_1_count   0.27886    0.09129   3.055  0.00238 ** 
## category_code_LT01_3_count   0.34678    0.11374   3.049  0.00242 ** 
## category_code_LT01_4_count   0.81169    0.08951   9.068  < 2e-16 ***
## category_code_LT01_5_count   0.93866    0.06198  15.144  < 2e-16 ***
## category_code_LT01_13_count  0.01127    0.24611   0.046  0.96350    
## category_code_LT01_15_count -0.38985    0.76677  -0.508  0.61138    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6279, Adjusted R-squared:  0.6233 
## F-statistic: 138.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 0.623589899214743 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0007 -0.7552  0.0251  0.8464  3.4383 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96561    0.08744 113.975  < 2e-16 ***
## category_code_LT01_1_count   0.27263    0.08991   3.032  0.00256 ** 
## category_code_LT01_3_count   0.32922    0.11395   2.889  0.00403 ** 
## category_code_LT01_4_count   0.81150    0.08948   9.069  < 2e-16 ***
## category_code_LT01_5_count   0.93811    0.06197  15.139  < 2e-16 ***
## category_code_LT01_13_count  0.02846    0.24516   0.116  0.90763    
## category_code_LT01_16_count  0.89186    1.17019   0.762  0.44634    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6236 
## F-statistic: 138.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 0.623391409226731 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9996 -0.7548  0.0321  0.8547  3.4400 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96526    0.08759 113.774  < 2e-16 ***
## category_code_LT01_1_count   0.27701    0.09075   3.053  0.00239 ** 
## category_code_LT01_3_count   0.34841    0.11389   3.059  0.00234 ** 
## category_code_LT01_4_count   0.80827    0.09045   8.936  < 2e-16 ***
## category_code_LT01_5_count   0.93693    0.06235  15.027  < 2e-16 ***
## category_code_LT01_14_count  0.08407    0.32887   0.256  0.79834    
## category_code_LT01_15_count -0.39288    0.76363  -0.514  0.60715    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6279, Adjusted R-squared:  0.6234 
## F-statistic: 138.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 0.623642632691261 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0006 -0.7563  0.0147  0.8712  3.4391 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96677    0.08754 113.859  < 2e-16 ***
## category_code_LT01_1_count   0.27132    0.08956   3.029  0.00258 ** 
## category_code_LT01_3_count   0.33089    0.11408   2.900  0.00389 ** 
## category_code_LT01_4_count   0.80807    0.09043   8.936  < 2e-16 ***
## category_code_LT01_5_count   0.93630    0.06234  15.019  < 2e-16 ***
## category_code_LT01_14_count  0.09438    0.32902   0.287  0.77436    
## category_code_LT01_16_count  0.90104    1.17046   0.770  0.44178    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6236 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 0.623759963238788 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9995 -0.7540  0.0212  0.8551  3.4396 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96449    0.08744 113.960  < 2e-16 ***
## category_code_LT01_1_count   0.28112    0.09021   3.116  0.00194 ** 
## category_code_LT01_3_count   0.33563    0.11467   2.927  0.00358 ** 
## category_code_LT01_4_count   0.81215    0.08924   9.101  < 2e-16 ***
## category_code_LT01_5_count   0.93800    0.06192  15.149  < 2e-16 ***
## category_code_LT01_15_count -0.37063    0.76386  -0.485  0.62775    
## category_code_LT01_16_count  0.86502    1.17025   0.739  0.46015    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6283, Adjusted R-squared:  0.6238 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 0.601447994408199 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0445 -0.8250  0.0262  0.9134  3.6604 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97879    0.09008 110.776  < 2e-16 ***
## category_code_LT01_1_count  0.44103    0.08653   5.097 4.94e-07 ***
## category_code_LT01_3_count  0.60512    0.10699   5.656 2.63e-08 ***
## category_code_LT01_5_count  0.98218    0.06412  15.317  < 2e-16 ***
## category_code_LT01_6_count  0.69970    0.14949   4.681 3.71e-06 ***
## category_code_LT01_7_count  0.75413    0.15204   4.960 9.72e-07 ***
## category_code_LT01_8_count -0.26056    0.28181  -0.925    0.356    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.422 on 491 degrees of freedom
## Multiple R-squared:  0.6063, Adjusted R-squared:  0.6014 
## F-statistic:   126 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 0.60283595125245 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0281 -0.8360  0.0455  0.9489  3.6800 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97311    0.08993 110.903  < 2e-16 ***
## category_code_LT01_1_count  0.43369    0.08644   5.017 7.34e-07 ***
## category_code_LT01_3_count  0.57426    0.10847   5.294 1.81e-07 ***
## category_code_LT01_5_count  0.96675    0.06350  15.224  < 2e-16 ***
## category_code_LT01_6_count  0.67961    0.14949   4.546 6.89e-06 ***
## category_code_LT01_7_count  0.72237    0.15276   4.729 2.96e-06 ***
## category_code_LT01_9_count  0.37467    0.23354   1.604    0.109    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.419 on 491 degrees of freedom
## Multiple R-squared:  0.6076, Adjusted R-squared:  0.6028 
## F-statistic: 126.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 0.600875715822414 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0274 -0.8153  0.0372  0.9394  3.6814 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96719    0.09346 106.646  < 2e-16 ***
## category_code_LT01_1_count   0.44154    0.08673   5.091 5.08e-07 ***
## category_code_LT01_3_count   0.59679    0.10898   5.476 6.95e-08 ***
## category_code_LT01_5_count   0.97425    0.06352  15.336  < 2e-16 ***
## category_code_LT01_6_count   0.68613    0.15148   4.530 7.43e-06 ***
## category_code_LT01_7_count   0.74577    0.15266   4.885 1.40e-06 ***
## category_code_LT01_10_count  0.04591    0.11871   0.387    0.699    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.423 on 491 degrees of freedom
## Multiple R-squared:  0.6057, Adjusted R-squared:  0.6009 
## F-statistic: 125.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 0.613140111671994 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0351 -0.7941  0.0641  0.9160  3.4068 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98633    0.08876 112.515  < 2e-16 ***
## category_code_LT01_1_count   0.35397    0.08793   4.026 6.58e-05 ***
## category_code_LT01_3_count   0.44477    0.11286   3.941 9.29e-05 ***
## category_code_LT01_5_count   0.95776    0.06266  15.286  < 2e-16 ***
## category_code_LT01_6_count   0.55000    0.15172   3.625 0.000319 ***
## category_code_LT01_7_count   0.54731    0.15830   3.457 0.000593 ***
## category_code_LT01_11_count  0.45714    0.11530   3.965 8.44e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6178, Adjusted R-squared:  0.6131 
## F-statistic: 132.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 0.600929923338074 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0346 -0.8267  0.0305  0.9300  3.6718 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97683    0.09011 110.715  < 2e-16 ***
## category_code_LT01_1_count   0.43378    0.08746   4.960 9.73e-07 ***
## category_code_LT01_3_count   0.60014    0.10750   5.583 3.92e-08 ***
## category_code_LT01_5_count   0.97073    0.06383  15.208  < 2e-16 ***
## category_code_LT01_6_count   0.68600    0.15091   4.546 6.90e-06 ***
## category_code_LT01_7_count   0.74929    0.15213   4.925 1.15e-06 ***
## category_code_LT01_12_count  0.09910    0.21308   0.465    0.642    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.423 on 491 degrees of freedom
## Multiple R-squared:  0.6057, Adjusted R-squared:  0.6009 
## F-statistic: 125.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 0.600763232237565 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0365 -0.8248  0.0253  0.9247  3.6651 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97682    0.09013 110.691  < 2e-16 ***
## category_code_LT01_1_count   0.43814    0.08763   5.000 8.00e-07 ***
## category_code_LT01_3_count   0.60446    0.10709   5.644 2.81e-08 ***
## category_code_LT01_5_count   0.97345    0.06357  15.314  < 2e-16 ***
## category_code_LT01_6_count   0.69570    0.14956   4.652 4.24e-06 ***
## category_code_LT01_7_count   0.74879    0.15330   4.884 1.41e-06 ***
## category_code_LT01_13_count  0.02685    0.25369   0.106    0.916    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.423 on 491 degrees of freedom
## Multiple R-squared:  0.6056, Adjusted R-squared:  0.6008 
## F-statistic: 125.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 0.602197982769861 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0325 -0.8167  0.0384  0.9369  3.6537 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98125    0.09003 110.864  < 2e-16 ***
## category_code_LT01_1_count   0.41961    0.08772   4.784 2.28e-06 ***
## category_code_LT01_3_count   0.60210    0.10690   5.632 3.00e-08 ***
## category_code_LT01_5_count   0.96134    0.06408  15.003  < 2e-16 ***
## category_code_LT01_6_count   0.70575    0.14948   4.721 3.06e-06 ***
## category_code_LT01_7_count   0.72806    0.15280   4.765 2.49e-06 ***
## category_code_LT01_14_count  0.44855    0.33600   1.335    0.183    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.421 on 491 degrees of freedom
## Multiple R-squared:  0.607,  Adjusted R-squared:  0.6022 
## F-statistic: 126.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 0.600889704272981 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0354 -0.8248  0.0170  0.9237  3.6649 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97582    0.09015 110.662  < 2e-16 ***
## category_code_LT01_1_count   0.44586    0.08794   5.070 5.64e-07 ***
## category_code_LT01_3_count   0.60995    0.10784   5.656 2.64e-08 ***
## category_code_LT01_5_count   0.97339    0.06351  15.326  < 2e-16 ***
## category_code_LT01_6_count   0.69738    0.14960   4.662 4.05e-06 ***
## category_code_LT01_7_count   0.74776    0.15228   4.910 1.24e-06 ***
## category_code_LT01_15_count -0.32155    0.78733  -0.408    0.683    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.423 on 491 degrees of freedom
## Multiple R-squared:  0.6057, Adjusted R-squared:  0.6009 
## F-statistic: 125.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 0.60167193558739 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0352 -0.8242  0.0290  0.9289  3.6573 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97669    0.09003 110.817  < 2e-16 ***
## category_code_LT01_1_count   0.44144    0.08651   5.103 4.79e-07 ***
## category_code_LT01_3_count   0.58665    0.10829   5.417 9.49e-08 ***
## category_code_LT01_5_count   0.97178    0.06347  15.310  < 2e-16 ***
## category_code_LT01_6_count   0.70708    0.14978   4.721 3.07e-06 ***
## category_code_LT01_7_count   0.74997    0.15195   4.935 1.10e-06 ***
## category_code_LT01_16_count  1.28313    1.20635   1.064    0.288    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.421 on 491 degrees of freedom
## Multiple R-squared:  0.6065, Adjusted R-squared:  0.6017 
## F-statistic: 126.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 0.604013115044621 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0569 -0.7826  0.0503  0.9203  3.4017 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99150    0.08981 111.246  < 2e-16 ***
## category_code_LT01_1_count   0.38943    0.08847   4.402 1.32e-05 ***
## category_code_LT01_3_count   0.46264    0.11411   4.054 5.85e-05 ***
## category_code_LT01_5_count   0.98173    0.06388  15.368  < 2e-16 ***
## category_code_LT01_6_count   0.55585    0.15363   3.618 0.000328 ***
## category_code_LT01_8_count  -0.16892    0.28105  -0.601 0.548093    
## category_code_LT01_11_count  0.58377    0.11043   5.286 1.88e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6088, Adjusted R-squared:  0.604 
## F-statistic: 127.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 0.606271317011426 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0415 -0.7972  0.0686  0.9377  3.4073 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98583    0.08957 111.490  < 2e-16 ***
## category_code_LT01_1_count   0.38096    0.08824   4.317 1.91e-05 ***
## category_code_LT01_3_count   0.42954    0.11512   3.731 0.000213 ***
## category_code_LT01_5_count   0.96768    0.06316  15.322  < 2e-16 ***
## category_code_LT01_6_count   0.53699    0.15329   3.503 0.000502 ***
## category_code_LT01_9_count   0.41298    0.23161   1.783 0.075189 .  
## category_code_LT01_11_count  0.57166    0.11034   5.181 3.23e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.413 on 491 degrees of freedom
## Multiple R-squared:  0.611,  Adjusted R-squared:  0.6063 
## F-statistic: 128.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 0.604164857437361 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0338 -0.7821  0.0326  0.9333  3.4212 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97197    0.09309 107.119  < 2e-16 ***
## category_code_LT01_1_count   0.39047    0.08848   4.413 1.25e-05 ***
## category_code_LT01_3_count   0.44527    0.11602   3.838 0.000140 ***
## category_code_LT01_5_count   0.97663    0.06316  15.463  < 2e-16 ***
## category_code_LT01_6_count   0.53371    0.15544   3.434 0.000646 ***
## category_code_LT01_10_count  0.08733    0.11780   0.741 0.458833    
## category_code_LT01_11_count  0.58534    0.11034   5.305 1.71e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6089, Adjusted R-squared:  0.6042 
## F-statistic: 127.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 0.604153947408186 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0546 -0.7801  0.0279  0.9286  3.4026 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99055    0.08977 111.285  < 2e-16 ***
## category_code_LT01_1_count   0.39240    0.08864   4.427 1.18e-05 ***
## category_code_LT01_3_count   0.46045    0.11406   4.037 6.28e-05 ***
## category_code_LT01_5_count   0.97982    0.06337  15.462  < 2e-16 ***
## category_code_LT01_6_count   0.56037    0.15389   3.641   0.0003 ***
## category_code_LT01_11_count  0.60649    0.11369   5.334 1.47e-07 ***
## category_code_LT01_12_count -0.16008    0.21864  -0.732   0.4644    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6089, Adjusted R-squared:  0.6042 
## F-statistic: 127.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 0.603838869539471 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0510 -0.7946  0.0371  0.9270  3.4028 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99035    0.08981 111.239  < 2e-16 ***
## category_code_LT01_1_count   0.38232    0.08951   4.271 2.34e-05 ***
## category_code_LT01_3_count   0.46052    0.11411   4.036 6.31e-05 ***
## category_code_LT01_5_count   0.97489    0.06325  15.414  < 2e-16 ***
## category_code_LT01_6_count   0.55303    0.15355   3.602 0.000349 ***
## category_code_LT01_11_count  0.58370    0.11060   5.278 1.97e-07 ***
## category_code_LT01_13_count  0.09572    0.25127   0.381 0.703402    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 491 degrees of freedom
## Multiple R-squared:  0.6086, Adjusted R-squared:  0.6038 
## F-statistic: 127.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 0.605185496418345 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0470 -0.7972  0.0262  0.9178  3.3988 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99438    0.08971 111.409  < 2e-16 ***
## category_code_LT01_1_count   0.36848    0.08941   4.121 4.42e-05 ***
## category_code_LT01_3_count   0.46175    0.11391   4.054 5.87e-05 ***
## category_code_LT01_5_count   0.96334    0.06377  15.107  < 2e-16 ***
## category_code_LT01_6_count   0.56575    0.15361   3.683 0.000256 ***
## category_code_LT01_11_count  0.57115    0.11076   5.156 3.66e-07 ***
## category_code_LT01_14_count  0.45116    0.33439   1.349 0.177897    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 491 degrees of freedom
## Multiple R-squared:   0.61,  Adjusted R-squared:  0.6052 
## F-statistic:   128 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 0.604059379423528 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0496 -0.7861  0.0282  0.9269  3.4044 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98873    0.08981 111.215  < 2e-16 ***
## category_code_LT01_1_count   0.39698    0.08959   4.431 1.16e-05 ***
## category_code_LT01_3_count   0.46878    0.11471   4.087 5.11e-05 ***
## category_code_LT01_5_count   0.97527    0.06317  15.438  < 2e-16 ***
## category_code_LT01_6_count   0.55456    0.15354   3.612 0.000335 ***
## category_code_LT01_11_count  0.58632    0.11034   5.314 1.63e-07 ***
## category_code_LT01_15_count -0.50680    0.78326  -0.647 0.517910    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6088, Adjusted R-squared:  0.6041 
## F-statistic: 127.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 0.60441639099864 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0504 -0.7797  0.0533  0.9264  3.4031 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99010    0.08974 111.318  < 2e-16 ***
## category_code_LT01_1_count   0.38991    0.08840   4.411 1.27e-05 ***
## category_code_LT01_3_count   0.44653    0.11508   3.880 0.000119 ***
## category_code_LT01_5_count   0.97446    0.06315  15.430  < 2e-16 ***
## category_code_LT01_6_count   0.56315    0.15389   3.659 0.000280 ***
## category_code_LT01_11_count  0.58321    0.11035   5.285 1.89e-07 ***
## category_code_LT01_16_count  1.11679    1.20275   0.929 0.353591    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6092, Adjusted R-squared:  0.6044 
## F-statistic: 127.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 0.603060461281095 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0876 -0.8023  0.1131  0.8617  3.3804 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01271    0.08966 111.670  < 2e-16 ***
## category_code_LT01_1_count   0.39264    0.08852   4.435 1.13e-05 ***
## category_code_LT01_3_count   0.50280    0.11328   4.439 1.12e-05 ***
## category_code_LT01_5_count   0.99547    0.06358  15.657  < 2e-16 ***
## category_code_LT01_7_count   0.55311    0.16047   3.447 0.000616 ***
## category_code_LT01_8_count  -0.16402    0.28135  -0.583 0.560185    
## category_code_LT01_11_count  0.55553    0.11342   4.898 1.32e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.419 on 491 degrees of freedom
## Multiple R-squared:  0.6079, Adjusted R-squared:  0.6031 
## F-statistic: 126.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 0.604972663100464 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0724 -0.8085  0.1105  0.8792  3.3864 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00680    0.08946 111.859  < 2e-16 ***
## category_code_LT01_1_count   0.38531    0.08832   4.363 1.57e-05 ***
## category_code_LT01_3_count   0.47105    0.11441   4.117 4.50e-05 ***
## category_code_LT01_5_count   0.98213    0.06285  15.626  < 2e-16 ***
## category_code_LT01_7_count   0.52371    0.16072   3.258   0.0012 ** 
## category_code_LT01_9_count   0.38373    0.23275   1.649   0.0998 .  
## category_code_LT01_11_count  0.54809    0.11322   4.841 1.73e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 491 degrees of freedom
## Multiple R-squared:  0.6097, Adjusted R-squared:  0.605 
## F-statistic: 127.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 0.603614433714735 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0564 -0.7907  0.0647  0.8854  3.4076 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98556    0.09311 107.240  < 2e-16 ***
## category_code_LT01_1_count   0.39392    0.08846   4.453 1.05e-05 ***
## category_code_LT01_3_count   0.47750    0.11550   4.134 4.19e-05 ***
## category_code_LT01_5_count   0.98968    0.06279  15.762  < 2e-16 ***
## category_code_LT01_7_count   0.53560    0.16082   3.330 0.000932 ***
## category_code_LT01_10_count  0.11835    0.11682   1.013 0.311475    
## category_code_LT01_11_count  0.55553    0.11327   4.904 1.28e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 491 degrees of freedom
## Multiple R-squared:  0.6084, Adjusted R-squared:  0.6036 
## F-statistic: 127.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 0.602837005987263 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0837 -0.8012  0.1120  0.8654  3.3816 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01160    0.08966 111.657  < 2e-16 ***
## category_code_LT01_1_count   0.39283    0.08885   4.421 1.21e-05 ***
## category_code_LT01_3_count   0.50112    0.11327   4.424 1.19e-05 ***
## category_code_LT01_5_count   0.99138    0.06316  15.697  < 2e-16 ***
## category_code_LT01_7_count   0.54700    0.16070   3.404 0.000719 ***
## category_code_LT01_11_count  0.56628    0.11777   4.809 2.03e-06 ***
## category_code_LT01_12_count -0.05510    0.21881  -0.252 0.801297    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.419 on 491 degrees of freedom
## Multiple R-squared:  0.6076, Adjusted R-squared:  0.6028 
## F-statistic: 126.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 0.602788380283109 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0824 -0.8009  0.1118  0.8662  3.3818 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01131    0.08967 111.652  < 2e-16 ***
## category_code_LT01_1_count   0.39156    0.08940   4.380 1.45e-05 ***
## category_code_LT01_3_count   0.50097    0.11327   4.423 1.20e-05 ***
## category_code_LT01_5_count   0.98993    0.06289  15.741  < 2e-16 ***
## category_code_LT01_7_count   0.55050    0.16137   3.411 0.000699 ***
## category_code_LT01_11_count  0.55838    0.11339   4.925 1.16e-06 ***
## category_code_LT01_13_count -0.01452    0.25308  -0.057 0.954275    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.419 on 491 degrees of freedom
## Multiple R-squared:  0.6076, Adjusted R-squared:  0.6028 
## F-statistic: 126.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 0.603333394011179 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0805 -0.8039  0.1122  0.8693  3.3788 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01434    0.08968 111.673  < 2e-16 ***
## category_code_LT01_1_count   0.38037    0.08935   4.257 2.48e-05 ***
## category_code_LT01_3_count   0.50258    0.11321   4.439 1.12e-05 ***
## category_code_LT01_5_count   0.98292    0.06337  15.512  < 2e-16 ***
## category_code_LT01_7_count   0.53851    0.16085   3.348 0.000876 ***
## category_code_LT01_11_count  0.55306    0.11346   4.875 1.47e-06 ***
## category_code_LT01_14_count  0.27631    0.33559   0.823 0.410703    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 491 degrees of freedom
## Multiple R-squared:  0.6081, Adjusted R-squared:  0.6033 
## F-statistic:   127 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 0.602901285287662 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0813 -0.8000  0.1081  0.8703  3.3826 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01055    0.08968 111.631  < 2e-16 ***
## category_code_LT01_1_count   0.39662    0.08980   4.417 1.23e-05 ***
## category_code_LT01_3_count   0.50574    0.11397   4.438 1.12e-05 ***
## category_code_LT01_5_count   0.98957    0.06285  15.746  < 2e-16 ***
## category_code_LT01_7_count   0.54638    0.16059   3.402 0.000723 ***
## category_code_LT01_11_count  0.55921    0.11337   4.932 1.11e-06 ***
## category_code_LT01_15_count -0.29681    0.78518  -0.378 0.705583    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.419 on 491 degrees of freedom
## Multiple R-squared:  0.6077, Adjusted R-squared:  0.6029 
## F-statistic: 126.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 0.603140529596933 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0821 -0.8012  0.1128  0.8642  3.3815 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01161    0.08962 111.706  < 2e-16 ***
## category_code_LT01_1_count   0.39298    0.08852   4.439 1.11e-05 ***
## category_code_LT01_3_count   0.49142    0.11413   4.306 2.01e-05 ***
## category_code_LT01_5_count   0.98916    0.06283  15.743  < 2e-16 ***
## category_code_LT01_7_count   0.55007    0.16033   3.431 0.000653 ***
## category_code_LT01_11_count  0.55730    0.11332   4.918 1.19e-06 ***
## category_code_LT01_16_count  0.79575    1.20103   0.663 0.507927    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.419 on 491 degrees of freedom
## Multiple R-squared:  0.6079, Adjusted R-squared:  0.6031 
## F-statistic: 126.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 0.631326525977464 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9928 -0.7582  0.0474  0.8725  3.8974 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96429    0.08663 115.023  < 2e-16 ***
## category_code_LT01_1_count  0.25997    0.08803   2.953  0.00330 ** 
## category_code_LT01_4_count  0.75687    0.08776   8.624  < 2e-16 ***
## category_code_LT01_5_count  0.92852    0.06224  14.918  < 2e-16 ***
## category_code_LT01_6_count  0.46485    0.14852   3.130  0.00185 ** 
## category_code_LT01_7_count  0.47740    0.15228   3.135  0.00182 ** 
## category_code_LT01_8_count -0.21503    0.27108  -0.793  0.42802    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6358, Adjusted R-squared:  0.6313 
## F-statistic: 142.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 0.633105160979736 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9762 -0.7692  0.0304  0.8887  3.9094 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95806    0.08643 115.216  < 2e-16 ***
## category_code_LT01_1_count  0.25162    0.08787   2.864  0.00437 ** 
## category_code_LT01_4_count  0.74129    0.08807   8.417 4.25e-16 ***
## category_code_LT01_5_count  0.91359    0.06159  14.834  < 2e-16 ***
## category_code_LT01_6_count  0.44321    0.14840   2.987  0.00296 ** 
## category_code_LT01_7_count  0.44619    0.15268   2.922  0.00363 ** 
## category_code_LT01_9_count  0.38593    0.22235   1.736  0.08325 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.364 on 491 degrees of freedom
## Multiple R-squared:  0.6375, Adjusted R-squared:  0.6331 
## F-statistic: 143.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 0.631396297382489 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9658 -0.7511  0.0345  0.8972  3.8143 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94204    0.08989 110.607  < 2e-16 ***
## category_code_LT01_1_count   0.26063    0.08804   2.960  0.00322 ** 
## category_code_LT01_4_count   0.75243    0.08799   8.551  < 2e-16 ***
## category_code_LT01_5_count   0.92169    0.06157  14.969  < 2e-16 ***
## category_code_LT01_6_count   0.43872    0.15062   2.913  0.00375 ** 
## category_code_LT01_7_count   0.46247    0.15280   3.027  0.00260 ** 
## category_code_LT01_10_count  0.09552    0.11239   0.850  0.39581    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6358, Adjusted R-squared:  0.6314 
## F-statistic: 142.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 0.635640799092721 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9893 -0.7494  0.0534  0.9021  3.7159 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96936    0.08613 115.743  < 2e-16 ***
## category_code_LT01_1_count   0.22249    0.08860   2.511  0.01236 *  
## category_code_LT01_4_count   0.65651    0.09595   6.842 2.33e-11 ***
## category_code_LT01_5_count   0.91613    0.06125  14.957  < 2e-16 ***
## category_code_LT01_6_count   0.39183    0.15001   2.612  0.00928 ** 
## category_code_LT01_7_count   0.37567    0.15619   2.405  0.01653 *  
## category_code_LT01_11_count  0.29195    0.11495   2.540  0.01140 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.36 on 491 degrees of freedom
## Multiple R-squared:   0.64,  Adjusted R-squared:  0.6356 
## F-statistic: 145.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 0.630877939017708 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9853 -0.7521  0.0584  0.8889  3.9017 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96255    0.08665 114.971  < 2e-16 ***
## category_code_LT01_1_count   0.25629    0.08868   2.890  0.00402 ** 
## category_code_LT01_4_count   0.75649    0.08822   8.575  < 2e-16 ***
## category_code_LT01_5_count   0.92029    0.06189  14.870  < 2e-16 ***
## category_code_LT01_6_count   0.45740    0.14958   3.058  0.00235 ** 
## category_code_LT01_7_count   0.47380    0.15231   3.111  0.00197 ** 
## category_code_LT01_12_count  0.03655    0.20505   0.178  0.85861    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6353, Adjusted R-squared:  0.6309 
## F-statistic: 142.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 0.630876303875989 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9862 -0.7520  0.0453  0.8849  3.8991 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96242    0.08666 114.967  < 2e-16 ***
## category_code_LT01_1_count   0.26018    0.08883   2.929  0.00356 ** 
## category_code_LT01_4_count   0.75867    0.08789   8.632  < 2e-16 ***
## category_code_LT01_5_count   0.92167    0.06165  14.951  < 2e-16 ***
## category_code_LT01_6_count   0.45999    0.14855   3.096  0.00207 ** 
## category_code_LT01_7_count   0.47675    0.15320   3.112  0.00197 ** 
## category_code_LT01_13_count -0.04200    0.24413  -0.172  0.86349    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6353, Adjusted R-squared:  0.6309 
## F-statistic: 142.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 0.630885382131593 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9858 -0.7529  0.0536  0.8887  3.9009 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96335    0.08674 114.859  < 2e-16 ***
## category_code_LT01_1_count   0.25629    0.08853   2.895  0.00396 ** 
## category_code_LT01_4_count   0.75530    0.08880   8.506  < 2e-16 ***
## category_code_LT01_5_count   0.91985    0.06204  14.826  < 2e-16 ***
## category_code_LT01_6_count   0.46356    0.14923   3.106  0.00200 ** 
## category_code_LT01_7_count   0.47197    0.15260   3.093  0.00210 ** 
## category_code_LT01_14_count  0.06681    0.32727   0.204  0.83834    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6353, Adjusted R-squared:  0.6309 
## F-statistic: 142.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 0.630876319927833 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9857 -0.7518  0.0452  0.8851  3.8988 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96222    0.08667 114.942  < 2e-16 ***
## category_code_LT01_1_count   0.26089    0.08946   2.916  0.00371 ** 
## category_code_LT01_4_count   0.75881    0.08793   8.630  < 2e-16 ***
## category_code_LT01_5_count   0.92129    0.06161  14.952  < 2e-16 ***
## category_code_LT01_6_count   0.46161    0.14863   3.106  0.00201 ** 
## category_code_LT01_7_count   0.47278    0.15245   3.101  0.00204 ** 
## category_code_LT01_15_count -0.12954    0.75274  -0.172  0.86344    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6353, Adjusted R-squared:  0.6309 
## F-statistic: 142.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 0.632172813232769 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9833 -0.7514  0.0522  0.8916  3.9004 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96183    0.08650 115.163  < 2e-16 ***
## category_code_LT01_1_count   0.25914    0.08790   2.948  0.00335 ** 
## category_code_LT01_4_count   0.74869    0.08793   8.514  < 2e-16 ***
## category_code_LT01_5_count   0.91835    0.06155  14.921  < 2e-16 ***
## category_code_LT01_6_count   0.47241    0.14852   3.181  0.00156 ** 
## category_code_LT01_7_count   0.47279    0.15204   3.110  0.00198 ** 
## category_code_LT01_16_count  1.52402    1.14866   1.327  0.18520    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.366 on 491 degrees of freedom
## Multiple R-squared:  0.6366, Adjusted R-squared:  0.6322 
## F-statistic: 143.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 0.627162515465525 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9876 -0.7750  0.0375  0.9196  3.8927 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95748    0.08715 114.258  < 2e-16 ***
## category_code_LT01_1_count  0.27660    0.08825   3.134  0.00183 ** 
## category_code_LT01_4_count  0.82080    0.08436   9.730  < 2e-16 ***
## category_code_LT01_5_count  0.93083    0.06265  14.859  < 2e-16 ***
## category_code_LT01_6_count  0.44884    0.14969   2.999  0.00285 ** 
## category_code_LT01_8_count -0.20718    0.27261  -0.760  0.44762    
## category_code_LT01_9_count  0.45894    0.22301   2.058  0.04013 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6317, Adjusted R-squared:  0.6272 
## F-statistic: 140.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 0.62491140842673 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9723 -0.7688  0.0596  0.9541  3.7670 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93542    0.09065 109.598  < 2e-16 ***
## category_code_LT01_1_count   0.28853    0.08842   3.263  0.00118 ** 
## category_code_LT01_4_count   0.83664    0.08415   9.943  < 2e-16 ***
## category_code_LT01_5_count   0.94060    0.06266  15.010  < 2e-16 ***
## category_code_LT01_6_count   0.44042    0.15202   2.897  0.00393 ** 
## category_code_LT01_8_count  -0.19591    0.27335  -0.717  0.47391    
## category_code_LT01_10_count  0.12693    0.11295   1.124  0.26168    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6294, Adjusted R-squared:  0.6249 
## F-statistic:   139 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 0.63161436210721 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0004 -0.7606  0.0626  0.8781  3.6594 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97109    0.08663 115.094  < 2e-16 ***
## category_code_LT01_1_count   0.23537    0.08902   2.644  0.00846 ** 
## category_code_LT01_4_count   0.69975    0.09482   7.379 6.84e-13 ***
## category_code_LT01_5_count   0.92979    0.06219  14.951  < 2e-16 ***
## category_code_LT01_6_count   0.38329    0.15088   2.540  0.01138 *  
## category_code_LT01_8_count  -0.16159    0.27101  -0.596  0.55129    
## category_code_LT01_11_count  0.35819    0.11205   3.197  0.00148 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6361, Adjusted R-squared:  0.6316 
## F-statistic:   143 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 0.62398056927731 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9985 -0.7723  0.0467  0.9438  3.8826 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96260    0.08749 113.877  < 2e-16 ***
## category_code_LT01_1_count   0.28382    0.08914   3.184  0.00154 ** 
## category_code_LT01_4_count   0.84509    0.08421  10.036  < 2e-16 ***
## category_code_LT01_5_count   0.93916    0.06299  14.909  < 2e-16 ***
## category_code_LT01_6_count   0.46577    0.15105   3.084  0.00216 ** 
## category_code_LT01_8_count  -0.19220    0.27377  -0.702  0.48298    
## category_code_LT01_12_count  0.04351    0.20704   0.210  0.83362    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.624 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 0.623957747137569 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9991 -0.7664  0.0361  0.9477  3.8820 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96262    0.08749 113.872  < 2e-16 ***
## category_code_LT01_1_count   0.28452    0.08943   3.181  0.00156 ** 
## category_code_LT01_4_count   0.84609    0.08404  10.067  < 2e-16 ***
## category_code_LT01_5_count   0.93999    0.06281  14.965  < 2e-16 ***
## category_code_LT01_6_count   0.46989    0.15002   3.132  0.00184 ** 
## category_code_LT01_8_count  -0.18850    0.27419  -0.687  0.49211    
## category_code_LT01_13_count  0.02942    0.24545   0.120  0.90464    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.624 
## F-statistic: 138.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 0.624072511306694 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9988 -0.7774  0.0430  0.9389  3.8821 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96422    0.08757 113.785  < 2e-16 ***
## category_code_LT01_1_count   0.28210    0.08903   3.169  0.00163 ** 
## category_code_LT01_4_count   0.84078    0.08510   9.879  < 2e-16 ***
## category_code_LT01_5_count   0.93733    0.06317  14.837  < 2e-16 ***
## category_code_LT01_6_count   0.47549    0.15068   3.156  0.00170 ** 
## category_code_LT01_8_count  -0.19221    0.27365  -0.702  0.48276    
## category_code_LT01_14_count  0.13362    0.32967   0.405  0.68543    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6241 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 0.624016195708244 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9986 -0.7672  0.0389  0.9444  3.8783 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96201    0.08750 113.851  < 2e-16 ***
## category_code_LT01_1_count   0.29074    0.08986   3.236  0.00130 ** 
## category_code_LT01_4_count   0.84796    0.08382  10.117  < 2e-16 ***
## category_code_LT01_5_count   0.94020    0.06274  14.986  < 2e-16 ***
## category_code_LT01_6_count   0.47131    0.15009   3.140  0.00179 ** 
## category_code_LT01_8_count  -0.19017    0.27364  -0.695  0.48740    
## category_code_LT01_15_count -0.22858    0.75899  -0.301  0.76342    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.624 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 0.625380322540276 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9970 -0.7755  0.0440  0.9573  3.8808 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96199    0.08732 114.082  < 2e-16 ***
## category_code_LT01_1_count   0.28718    0.08834   3.251  0.00123 ** 
## category_code_LT01_4_count   0.83694    0.08391   9.974  < 2e-16 ***
## category_code_LT01_5_count   0.93787    0.06265  14.970  < 2e-16 ***
## category_code_LT01_6_count   0.48227    0.14999   3.215  0.00139 ** 
## category_code_LT01_8_count  -0.21038    0.27353  -0.769  0.44219    
## category_code_LT01_16_count  1.59119    1.16082   1.371  0.17108    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6254 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 0.627303627404525 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9606 -0.7821  0.0370  0.9370  3.8060 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93490    0.09035 109.964  < 2e-16 ***
## category_code_LT01_1_count   0.27718    0.08824   3.141  0.00178 ** 
## category_code_LT01_4_count   0.81487    0.08468   9.623  < 2e-16 ***
## category_code_LT01_5_count   0.92451    0.06198  14.917  < 2e-16 ***
## category_code_LT01_6_count   0.42321    0.15162   2.791  0.00546 ** 
## category_code_LT01_9_count   0.43006    0.22454   1.915  0.05603 .  
## category_code_LT01_10_count  0.09912    0.11342   0.874  0.38259    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6318, Adjusted R-squared:  0.6273 
## F-statistic: 140.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 0.633747231617325 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9847 -0.7609  0.0697  0.9014  3.6809 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96490    0.08640 115.334  < 2e-16 ***
## category_code_LT01_1_count   0.22758    0.08878   2.563  0.01066 *  
## category_code_LT01_4_count   0.68341    0.09495   7.197 2.31e-12 ***
## category_code_LT01_5_count   0.91598    0.06149  14.897  < 2e-16 ***
## category_code_LT01_6_count   0.36528    0.15053   2.427  0.01559 *  
## category_code_LT01_9_count   0.39763    0.22170   1.794  0.07350 .  
## category_code_LT01_11_count  0.34380    0.11204   3.068  0.00227 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.363 on 491 degrees of freedom
## Multiple R-squared:  0.6382, Adjusted R-squared:  0.6337 
## F-statistic: 144.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 0.626746660185078 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9805 -0.8010  0.0561  0.9300  3.8968 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95588    0.08717 114.210  < 2e-16 ***
## category_code_LT01_1_count   0.27295    0.08890   3.070  0.00226 ** 
## category_code_LT01_4_count   0.82005    0.08483   9.667  < 2e-16 ***
## category_code_LT01_5_count   0.92292    0.06229  14.816  < 2e-16 ***
## category_code_LT01_6_count   0.44183    0.15075   2.931  0.00354 ** 
## category_code_LT01_9_count   0.45357    0.22305   2.034  0.04254 *  
## category_code_LT01_12_count  0.03566    0.20620   0.173  0.86275    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6267 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 0.626790300174743 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9807 -0.7941  0.0564  0.9280  3.8981 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95600    0.08717 114.216  < 2e-16 ***
## category_code_LT01_1_count   0.27097    0.08920   3.038  0.00251 ** 
## category_code_LT01_4_count   0.81923    0.08476   9.666  < 2e-16 ***
## category_code_LT01_5_count   0.92313    0.06207  14.871  < 2e-16 ***
## category_code_LT01_6_count   0.44571    0.14969   2.977  0.00305 ** 
## category_code_LT01_9_count   0.45817    0.22349   2.050  0.04089 *  
## category_code_LT01_13_count  0.07227    0.24456   0.296  0.76772    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 0.626772690245584 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9810 -0.7953  0.0589  0.9278  3.8961 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95693    0.08727 114.092  < 2e-16 ***
## category_code_LT01_1_count   0.27239    0.08877   3.069  0.00227 ** 
## category_code_LT01_4_count   0.81793    0.08559   9.556  < 2e-16 ***
## category_code_LT01_5_count   0.92210    0.06244  14.769  < 2e-16 ***
## category_code_LT01_6_count   0.44881    0.15046   2.983  0.00300 ** 
## category_code_LT01_9_count   0.44991    0.22359   2.012  0.04474 *  
## category_code_LT01_14_count  0.08340    0.32927   0.253  0.80014    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 0.626770240523491 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9807 -0.7791  0.0521  0.9212  3.8933 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95542    0.08719 114.186  < 2e-16 ***
## category_code_LT01_1_count   0.27865    0.08964   3.109  0.00199 ** 
## category_code_LT01_4_count   0.82247    0.08448   9.736  < 2e-16 ***
## category_code_LT01_5_count   0.92386    0.06202  14.897  < 2e-16 ***
## category_code_LT01_6_count   0.44646    0.14980   2.980  0.00302 ** 
## category_code_LT01_9_count   0.45232    0.22312   2.027  0.04318 *  
## category_code_LT01_15_count -0.18675    0.75651  -0.247  0.80512    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 0.627873528222063 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9789 -0.7941  0.0649  0.9320  3.8953 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95536    0.08704 114.376  < 2e-16 ***
## category_code_LT01_1_count   0.27593    0.08814   3.131  0.00185 ** 
## category_code_LT01_4_count   0.81345    0.08453   9.624  < 2e-16 ***
## category_code_LT01_5_count   0.92143    0.06196  14.872  < 2e-16 ***
## category_code_LT01_6_count   0.45663    0.14976   3.049  0.00242 ** 
## category_code_LT01_9_count   0.43956    0.22301   1.971  0.04928 *  
## category_code_LT01_16_count  1.42485    1.15691   1.232  0.21869    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6324, Adjusted R-squared:  0.6279 
## F-statistic: 140.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 0.63206752109405 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9719 -0.7519  0.0607  0.9076  3.5648 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94620    0.08985 110.702  < 2e-16 ***
## category_code_LT01_1_count   0.23635    0.08896   2.657  0.00815 ** 
## category_code_LT01_4_count   0.69230    0.09502   7.286 1.28e-12 ***
## category_code_LT01_5_count   0.92446    0.06146  15.043  < 2e-16 ***
## category_code_LT01_6_count   0.35543    0.15265   2.328  0.02030 *  
## category_code_LT01_10_count  0.10974    0.11196   0.980  0.32750    
## category_code_LT01_11_count  0.35555    0.11203   3.174  0.00160 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.366 on 491 degrees of freedom
## Multiple R-squared:  0.6365, Adjusted R-squared:  0.6321 
## F-statistic: 143.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 0.62453689942745 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9659 -0.7815  0.0626  0.9625  3.7728 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93427    0.09069 109.547  < 2e-16 ***
## category_code_LT01_1_count   0.28504    0.08908   3.200  0.00146 ** 
## category_code_LT01_4_count   0.83590    0.08461   9.880  < 2e-16 ***
## category_code_LT01_5_count   0.93307    0.06229  14.980  < 2e-16 ***
## category_code_LT01_6_count   0.43420    0.15298   2.838  0.00472 ** 
## category_code_LT01_10_count  0.12493    0.11306   1.105  0.26968    
## category_code_LT01_12_count  0.03163    0.20692   0.153  0.87856    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 0.62453030479267 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9664 -0.7729  0.0602  0.9608  3.7726 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93432    0.09069 109.536  < 2e-16 ***
## category_code_LT01_1_count   0.28514    0.08934   3.192  0.00151 ** 
## category_code_LT01_4_count   0.83638    0.08445   9.904  < 2e-16 ***
## category_code_LT01_5_count   0.93368    0.06205  15.046  < 2e-16 ***
## category_code_LT01_6_count   0.43735    0.15208   2.876  0.00420 ** 
## category_code_LT01_10_count  0.12500    0.11307   1.105  0.26950    
## category_code_LT01_13_count  0.02975    0.24496   0.121  0.90340    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 0.624532890637701 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9670 -0.7731  0.0639  0.9507  3.7749 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93549    0.09124 108.892  < 2e-16 ***
## category_code_LT01_1_count   0.28526    0.08906   3.203  0.00145 ** 
## category_code_LT01_4_count   0.83539    0.08524   9.800  < 2e-16 ***
## category_code_LT01_5_count   0.93292    0.06250  14.927  < 2e-16 ***
## category_code_LT01_6_count   0.43971    0.15351   2.864  0.00436 ** 
## category_code_LT01_10_count  0.12179    0.11633   1.047  0.29566    
## category_code_LT01_14_count  0.04566    0.33916   0.135  0.89295    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 0.6246389472956 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9648 -0.7655  0.0504  0.9496  3.7643 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93262    0.09075 109.454  < 2e-16 ***
## category_code_LT01_1_count   0.29294    0.08982   3.262  0.00119 ** 
## category_code_LT01_4_count   0.83825    0.08422   9.953  < 2e-16 ***
## category_code_LT01_5_count   0.93380    0.06200  15.061  < 2e-16 ***
## category_code_LT01_6_count   0.43835    0.15204   2.883  0.00411 ** 
## category_code_LT01_10_count  0.12916    0.11335   1.139  0.25506    
## category_code_LT01_15_count -0.30135    0.76087  -0.396  0.69223    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6292, Adjusted R-squared:  0.6246 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 0.625741081429574 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9656 -0.7781  0.0590  0.9538  3.7792 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93535    0.09054 109.734  < 2e-16 ***
## category_code_LT01_1_count   0.28739    0.08829   3.255  0.00121 ** 
## category_code_LT01_4_count   0.82871    0.08432   9.829  < 2e-16 ***
## category_code_LT01_5_count   0.93106    0.06195  15.029  < 2e-16 ***
## category_code_LT01_6_count   0.45026    0.15214   2.960  0.00323 ** 
## category_code_LT01_10_count  0.11667    0.11303   1.032  0.30249    
## category_code_LT01_16_count  1.46987    1.16086   1.266  0.20604    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6257 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 0.63161435702078 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9979 -0.7630  0.0646  0.8797  3.6457 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97015    0.08661 115.116  < 2e-16 ***
## category_code_LT01_1_count   0.23774    0.08925   2.664  0.00798 ** 
## category_code_LT01_4_count   0.69772    0.09485   7.356 8.01e-13 ***
## category_code_LT01_5_count   0.92741    0.06172  15.026  < 2e-16 ***
## category_code_LT01_6_count   0.38656    0.15121   2.556  0.01088 *  
## category_code_LT01_11_count  0.37689    0.11534   3.268  0.00116 ** 
## category_code_LT01_12_count -0.12580    0.21098  -0.596  0.55129    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6361, Adjusted R-squared:  0.6316 
## F-statistic:   143 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 0.63134887443075 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9953 -0.7588  0.0697  0.8826  3.6608 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.969847   0.086641 115.071  < 2e-16 ***
## category_code_LT01_1_count  0.233077   0.089799   2.596  0.00973 ** 
## category_code_LT01_4_count  0.698976   0.094994   7.358  7.9e-13 ***
## category_code_LT01_5_count  0.924169   0.061557  15.013  < 2e-16 ***
## category_code_LT01_6_count  0.379698   0.150868   2.517  0.01216 *  
## category_code_LT01_11_count 0.360251   0.112107   3.213  0.00140 ** 
## category_code_LT01_13_count 0.009848   0.242737   0.041  0.96765    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6358, Adjusted R-squared:  0.6313 
## F-statistic: 142.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 0.631422396749665 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9950 -0.7569  0.0608  0.8863  3.6618 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97107    0.08672 114.979  < 2e-16 ***
## category_code_LT01_1_count   0.23063    0.08948   2.577  0.01025 *  
## category_code_LT01_4_count   0.69482    0.09585   7.249 1.64e-12 ***
## category_code_LT01_5_count   0.92191    0.06196  14.880  < 2e-16 ***
## category_code_LT01_6_count   0.38431    0.15155   2.536  0.01153 *  
## category_code_LT01_11_count  0.35951    0.11205   3.208  0.00142 ** 
## category_code_LT01_14_count  0.10304    0.32650   0.316  0.75246    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6359, Adjusted R-squared:  0.6314 
## F-statistic: 142.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 0.631464717552564 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9945 -0.7571  0.0699  0.8825  3.6561 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96914    0.08664 115.060  < 2e-16 ***
## category_code_LT01_1_count   0.23949    0.09025   2.654  0.00822 ** 
## category_code_LT01_4_count   0.70003    0.09486   7.379 6.84e-13 ***
## category_code_LT01_5_count   0.92406    0.06151  15.023  < 2e-16 ***
## category_code_LT01_6_count   0.38156    0.15087   2.529  0.01175 *  
## category_code_LT01_11_count  0.36163    0.11205   3.227  0.00133 ** 
## category_code_LT01_15_count -0.29689    0.75171  -0.395  0.69305    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6359, Adjusted R-squared:  0.6315 
## F-statistic: 142.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 0.63236466240004 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9929 -0.7549  0.0755  0.8860  3.6649 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96903    0.08652 115.219  < 2e-16 ***
## category_code_LT01_1_count   0.23539    0.08890   2.648  0.00836 ** 
## category_code_LT01_4_count   0.69382    0.09483   7.316 1.05e-12 ***
## category_code_LT01_5_count   0.92181    0.06147  14.997  < 2e-16 ***
## category_code_LT01_6_count   0.39167    0.15096   2.595  0.00975 ** 
## category_code_LT01_11_count  0.35309    0.11205   3.151  0.00172 ** 
## category_code_LT01_16_count  1.34046    1.15015   1.165  0.24440    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.366 on 491 degrees of freedom
## Multiple R-squared:  0.6368, Adjusted R-squared:  0.6324 
## F-statistic: 143.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 0.623622743255976 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9923 -0.7646  0.0439  0.9492  3.8865 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96114    0.08750 113.840  < 2e-16 ***
## category_code_LT01_1_count   0.28026    0.09003   3.113  0.00196 ** 
## category_code_LT01_4_count   0.84459    0.08452   9.992  < 2e-16 ***
## category_code_LT01_5_count   0.93240    0.06241  14.941  < 2e-16 ***
## category_code_LT01_6_count   0.46286    0.15108   3.064  0.00231 ** 
## category_code_LT01_12_count  0.03884    0.20708   0.188  0.85131    
## category_code_LT01_13_count  0.03923    0.24511   0.160  0.87290    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6236 
## F-statistic: 138.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 0.623714464586381 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9921 -0.7616  0.0480  0.9495  3.8860 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96258    0.08758 113.751  < 2e-16 ***
## category_code_LT01_1_count   0.27882    0.08960   3.112  0.00197 ** 
## category_code_LT01_4_count   0.84015    0.08548   9.829  < 2e-16 ***
## category_code_LT01_5_count   0.93004    0.06277  14.818  < 2e-16 ***
## category_code_LT01_6_count   0.46840    0.15187   3.084  0.00216 ** 
## category_code_LT01_12_count  0.03329    0.20763   0.160  0.87269    
## category_code_LT01_14_count  0.12608    0.33075   0.381  0.70322    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6283, Adjusted R-squared:  0.6237 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 0.623670440489251 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9919 -0.7601  0.0536  0.9459  3.8825 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96049    0.08751 113.818  < 2e-16 ***
## category_code_LT01_1_count   0.28701    0.09058   3.169  0.00163 ** 
## category_code_LT01_4_count   0.84682    0.08432  10.043  < 2e-16 ***
## category_code_LT01_5_count   0.93272    0.06236  14.957  < 2e-16 ***
## category_code_LT01_6_count   0.46428    0.15118   3.071  0.00225 ** 
## category_code_LT01_12_count  0.03674    0.20722   0.177  0.85934    
## category_code_LT01_15_count -0.22526    0.76000  -0.296  0.76705    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6237 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 0.624952652787887 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9897 -0.7645  0.0463  0.9576  3.8852 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96032    0.08735 114.033  < 2e-16 ***
## category_code_LT01_1_count   0.28332    0.08900   3.183  0.00155 ** 
## category_code_LT01_4_count   0.83618    0.08440   9.908  < 2e-16 ***
## category_code_LT01_5_count   0.92981    0.06229  14.926  < 2e-16 ***
## category_code_LT01_6_count   0.47450    0.15105   3.141  0.00178 ** 
## category_code_LT01_12_count  0.03639    0.20670   0.176  0.86032    
## category_code_LT01_16_count  1.54177    1.15992   1.329  0.18440    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6295, Adjusted R-squared:  0.625 
## F-statistic:   139 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 0.623716874999607 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9926 -0.7613  0.0545  0.9518  3.8863 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96274    0.08759 113.749  < 2e-16 ***
## category_code_LT01_1_count   0.27824    0.08996   3.093  0.00209 ** 
## category_code_LT01_4_count   0.84013    0.08545   9.832  < 2e-16 ***
## category_code_LT01_5_count   0.93047    0.06259  14.866  < 2e-16 ***
## category_code_LT01_6_count   0.47209    0.15069   3.133  0.00183 ** 
## category_code_LT01_13_count  0.04163    0.24509   0.170  0.86520    
## category_code_LT01_14_count  0.13111    0.32984   0.398  0.69117    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6283, Adjusted R-squared:  0.6237 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 0.623660620822157 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9925 -0.7579  0.0388  0.9437  3.8823 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96057    0.08752 113.813  < 2e-16 ***
## category_code_LT01_1_count   0.28710    0.09096   3.156  0.00170 ** 
## category_code_LT01_4_count   0.84739    0.08418  10.067  < 2e-16 ***
## category_code_LT01_5_count   0.93344    0.06213  15.025  < 2e-16 ***
## category_code_LT01_6_count   0.46791    0.15009   3.118  0.00193 ** 
## category_code_LT01_13_count  0.03358    0.24603   0.136  0.89150    
## category_code_LT01_15_count -0.22172    0.76231  -0.291  0.77129    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6237 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 0.624961730166566 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9902 -0.7585  0.0437  0.9621  3.8856 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96043    0.08735 114.033  < 2e-16 ***
## category_code_LT01_1_count   0.28259    0.08925   3.166  0.00164 ** 
## category_code_LT01_4_count   0.83620    0.08426   9.923  < 2e-16 ***
## category_code_LT01_5_count   0.93033    0.06206  14.990  < 2e-16 ***
## category_code_LT01_6_count   0.47844    0.15000   3.190  0.00152 ** 
## category_code_LT01_13_count  0.05069    0.24478   0.207  0.83604    
## category_code_LT01_16_count  1.55187    1.16047   1.337  0.18175    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6295, Adjusted R-squared:  0.625 
## F-statistic:   139 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 0.623765129417426 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9921 -0.7613  0.0503  0.9468  3.8822 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96205    0.08760 113.728  < 2e-16 ***
## category_code_LT01_1_count   0.28515    0.09039   3.155  0.00171 ** 
## category_code_LT01_4_count   0.84242    0.08521   9.887  < 2e-16 ***
## category_code_LT01_5_count   0.93078    0.06253  14.884  < 2e-16 ***
## category_code_LT01_6_count   0.47327    0.15075   3.139  0.00179 ** 
## category_code_LT01_14_count  0.12984    0.32977   0.394  0.69396    
## category_code_LT01_15_count -0.23007    0.75924  -0.303  0.76200    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6283, Adjusted R-squared:  0.6238 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 0.625095183303817 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9898 -0.7546  0.0507  0.9641  3.8852 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96218    0.08742 113.955  < 2e-16 ***
## category_code_LT01_1_count   0.28065    0.08888   3.158  0.00169 ** 
## category_code_LT01_4_count   0.83044    0.08537   9.728  < 2e-16 ***
## category_code_LT01_5_count   0.92724    0.06248  14.840  < 2e-16 ***
## category_code_LT01_6_count   0.48473    0.15069   3.217  0.00138 ** 
## category_code_LT01_14_count  0.15380    0.32965   0.467  0.64102    
## category_code_LT01_16_count  1.57269    1.16127   1.354  0.17627    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6296, Adjusted R-squared:  0.6251 
## F-statistic: 139.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 0.624986561420473 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9898 -0.7586  0.0495  0.9559  3.8814 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95980    0.08736 114.008  < 2e-16 ***
## category_code_LT01_1_count   0.28947    0.08971   3.227  0.00134 ** 
## category_code_LT01_4_count   0.83868    0.08403   9.981  < 2e-16 ***
## category_code_LT01_5_count   0.93074    0.06201  15.008  < 2e-16 ***
## category_code_LT01_6_count   0.47927    0.15006   3.194  0.00149 ** 
## category_code_LT01_15_count -0.20819    0.75820  -0.275  0.78375    
## category_code_LT01_16_count  1.53674    1.16010   1.325  0.18590    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6295, Adjusted R-squared:  0.625 
## F-statistic:   139 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 0.626848410776012 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0136 -0.7668  0.0199  0.8578  3.8747 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97593    0.08702 114.634  < 2e-16 ***
## category_code_LT01_1_count  0.27592    0.08832   3.124  0.00189 ** 
## category_code_LT01_4_count  0.82906    0.08367   9.909  < 2e-16 ***
## category_code_LT01_5_count  0.94177    0.06238  15.097  < 2e-16 ***
## category_code_LT01_7_count  0.45094    0.15403   2.928  0.00357 ** 
## category_code_LT01_8_count -0.19982    0.27266  -0.733  0.46400    
## category_code_LT01_9_count  0.43552    0.22382   1.946  0.05225 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6314, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 0.625404912495034 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9909 -0.7688  0.0316  0.8849  3.7277 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94748    0.09062 109.768  < 2e-16 ***
## category_code_LT01_1_count   0.28637    0.08840   3.239  0.00128 ** 
## category_code_LT01_4_count   0.83584    0.08382   9.971  < 2e-16 ***
## category_code_LT01_5_count   0.95003    0.06232  15.243  < 2e-16 ***
## category_code_LT01_7_count   0.46358    0.15409   3.009  0.00276 ** 
## category_code_LT01_8_count  -0.19218    0.27313  -0.704  0.48199    
## category_code_LT01_10_count  0.15309    0.11166   1.371  0.17101    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6254 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 0.630826811841384 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0226 -0.7725  0.0255  0.8436  3.6525 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98630    0.08653 115.415  < 2e-16 ***
## category_code_LT01_1_count   0.23764    0.08909   2.667  0.00790 ** 
## category_code_LT01_4_count   0.71589    0.09391   7.623 1.29e-13 ***
## category_code_LT01_5_count   0.93976    0.06198  15.163  < 2e-16 ***
## category_code_LT01_7_count   0.36509    0.15723   2.322  0.02064 *  
## category_code_LT01_8_count  -0.15597    0.27125  -0.575  0.56555    
## category_code_LT01_11_count  0.34387    0.11388   3.020  0.00266 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6353, Adjusted R-squared:  0.6308 
## F-statistic: 142.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 0.624215594290056 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0228 -0.7709  0.0185  0.8726  3.8681 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98131    0.08728 114.355  < 2e-16 ***
## category_code_LT01_1_count   0.27773    0.08927   3.111  0.00197 ** 
## category_code_LT01_4_count   0.84505    0.08402  10.057  < 2e-16 ***
## category_code_LT01_5_count   0.94732    0.06275  15.097  < 2e-16 ***
## category_code_LT01_7_count   0.48179    0.15373   3.134  0.00183 ** 
## category_code_LT01_8_count  -0.18943    0.27365  -0.692  0.48913    
## category_code_LT01_12_count  0.11620    0.20552   0.565  0.57208    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6288, Adjusted R-squared:  0.6242 
## F-statistic: 138.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 0.624034164229971 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0259 -0.7710  0.0075  0.8698  3.8611 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98140    0.08731 114.328  < 2e-16 ***
## category_code_LT01_1_count   0.28759    0.08934   3.219  0.00137 ** 
## category_code_LT01_4_count   0.85287    0.08321  10.250  < 2e-16 ***
## category_code_LT01_5_count   0.95165    0.06248  15.231  < 2e-16 ***
## category_code_LT01_7_count   0.48707    0.15470   3.148  0.00174 ** 
## category_code_LT01_8_count  -0.18956    0.27417  -0.691  0.48965    
## category_code_LT01_13_count -0.07093    0.24686  -0.287  0.77399    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.624 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 0.623977532727547 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0256 -0.7707  0.0090  0.8749  3.8632 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98115    0.08743 114.161  < 2e-16 ***
## category_code_LT01_1_count   0.28498    0.08896   3.203  0.00145 ** 
## category_code_LT01_4_count   0.85291    0.08379  10.179  < 2e-16 ***
## category_code_LT01_5_count   0.95156    0.06277  15.158  < 2e-16 ***
## category_code_LT01_7_count   0.48306    0.15407   3.135  0.00182 ** 
## category_code_LT01_8_count  -0.18409    0.27360  -0.673  0.50137    
## category_code_LT01_14_count -0.03047    0.32875  -0.093  0.92618    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.624 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 0.62397233350502 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0255 -0.7711  0.0105  0.8769  3.8629 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98150    0.08733 114.302  < 2e-16 ***
## category_code_LT01_1_count   0.28489    0.09004   3.164  0.00165 ** 
## category_code_LT01_4_count   0.85221    0.08337  10.223  < 2e-16 ***
## category_code_LT01_5_count   0.95096    0.06244  15.230  < 2e-16 ***
## category_code_LT01_7_count   0.48191    0.15392   3.131  0.00185 ** 
## category_code_LT01_8_count  -0.18425    0.27360  -0.673  0.50098    
## category_code_LT01_15_count -0.03224    0.75915  -0.042  0.96615    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.624 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 0.625003124511615 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0244 -0.7708  0.0269  0.8689  3.8623 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98149    0.08719 114.479  < 2e-16 ***
## category_code_LT01_1_count   0.28576    0.08845   3.231  0.00132 ** 
## category_code_LT01_4_count   0.84584    0.08321  10.165  < 2e-16 ***
## category_code_LT01_5_count   0.94940    0.06237  15.223  < 2e-16 ***
## category_code_LT01_7_count   0.48158    0.15357   3.136  0.00182 ** 
## category_code_LT01_8_count  -0.20039    0.27356  -0.733  0.46421    
## category_code_LT01_16_count  1.34758    1.15918   1.163  0.24559    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6295, Adjusted R-squared:  0.625 
## F-statistic: 139.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 0.627412373787455 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9790 -0.7547  0.0261  0.8664  3.7645 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94628    0.09036 110.074  < 2e-16 ***
## category_code_LT01_1_count   0.27647    0.08825   3.133  0.00183 ** 
## category_code_LT01_4_count   0.81784    0.08424   9.709  < 2e-16 ***
## category_code_LT01_5_count   0.93470    0.06164  15.163  < 2e-16 ***
## category_code_LT01_7_count   0.43472    0.15431   2.817  0.00504 ** 
## category_code_LT01_9_count   0.39938    0.22527   1.773  0.07686 .  
## category_code_LT01_10_count  0.12698    0.11219   1.132  0.25825    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6319, Adjusted R-squared:  0.6274 
## F-statistic: 140.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 0.632820221817719 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0065 -0.7689  0.0373  0.8636  3.6723 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97962    0.08631 115.621  < 2e-16 ***
## category_code_LT01_1_count   0.23027    0.08886   2.591  0.00984 ** 
## category_code_LT01_4_count   0.70041    0.09404   7.448 4.29e-13 ***
## category_code_LT01_5_count   0.92614    0.06127  15.116  < 2e-16 ***
## category_code_LT01_7_count   0.33857    0.15727   2.153  0.03182 *  
## category_code_LT01_9_count   0.38522    0.22248   1.731  0.08399 .  
## category_code_LT01_11_count  0.33234    0.11378   2.921  0.00365 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.365 on 491 degrees of freedom
## Multiple R-squared:  0.6373, Adjusted R-squared:  0.6328 
## F-statistic: 143.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 0.626640672557767 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0046 -0.7635  0.0106  0.8539  3.8820 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97395    0.08702 114.619  < 2e-16 ***
## category_code_LT01_1_count   0.26827    0.08905   3.013  0.00272 ** 
## category_code_LT01_4_count   0.82340    0.08454   9.740  < 2e-16 ***
## category_code_LT01_5_count   0.93158    0.06206  15.010  < 2e-16 ***
## category_code_LT01_7_count   0.44770    0.15402   2.907  0.00382 ** 
## category_code_LT01_9_count   0.42886    0.22382   1.916  0.05593 .  
## category_code_LT01_12_count  0.10513    0.20477   0.513  0.60791    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6311, Adjusted R-squared:  0.6266 
## F-statistic:   140 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 0.626446796169234 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0073 -0.7646  0.0256  0.8470  3.8769 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97415    0.08704 114.592  < 2e-16 ***
## category_code_LT01_1_count   0.27524    0.08914   3.088  0.00213 ** 
## category_code_LT01_4_count   0.82993    0.08381   9.902  < 2e-16 ***
## category_code_LT01_5_count   0.93520    0.06176  15.142  < 2e-16 ***
## category_code_LT01_7_count   0.44966    0.15510   2.899  0.00391 ** 
## category_code_LT01_9_count   0.42911    0.22453   1.911  0.05657 .  
## category_code_LT01_13_count -0.02284    0.24628  -0.093  0.92613    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.631,  Adjusted R-squared:  0.6264 
## F-statistic: 139.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 0.626473909909137 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0071 -0.7642  0.0191  0.8617  3.8775 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97321    0.08716 114.418  < 2e-16 ***
## category_code_LT01_1_count   0.27585    0.08871   3.110  0.00198 ** 
## category_code_LT01_4_count   0.83158    0.08426   9.869  < 2e-16 ***
## category_code_LT01_5_count   0.93631    0.06204  15.092  < 2e-16 ***
## category_code_LT01_7_count   0.44979    0.15429   2.915  0.00372 ** 
## category_code_LT01_9_count   0.43344    0.22421   1.933  0.05379 .  
## category_code_LT01_14_count -0.06903    0.32819  -0.210  0.83348    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.631,  Adjusted R-squared:  0.6265 
## F-statistic: 139.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 0.626440275949939 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0072 -0.7645  0.0300  0.8493  3.8776 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.974194   0.087054 114.575  < 2e-16 ***
## category_code_LT01_1_count   0.274223   0.089831   3.053  0.00239 ** 
## category_code_LT01_4_count   0.829589   0.083937   9.884  < 2e-16 ***
## category_code_LT01_5_count   0.934996   0.061725  15.148  < 2e-16 ***
## category_code_LT01_7_count   0.447968   0.154190   2.905  0.00383 ** 
## category_code_LT01_9_count   0.430705   0.223903   1.924  0.05498 .  
## category_code_LT01_15_count -0.004386   0.756815  -0.006  0.99538    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.631,  Adjusted R-squared:  0.6264 
## F-statistic: 139.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 0.62726096024995 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0060 -0.7637  0.0391  0.8496  3.8767 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97415    0.08694 114.719  < 2e-16 ***
## category_code_LT01_1_count   0.27560    0.08825   3.123  0.00190 ** 
## category_code_LT01_4_count   0.82470    0.08375   9.847  < 2e-16 ***
## category_code_LT01_5_count   0.93336    0.06168  15.133  < 2e-16 ***
## category_code_LT01_7_count   0.44803    0.15389   2.911  0.00376 ** 
## category_code_LT01_9_count   0.41964    0.22386   1.875  0.06145 .  
## category_code_LT01_16_count  1.20147    1.15553   1.040  0.29896    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6318, Adjusted R-squared:  0.6273 
## F-statistic: 140.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 0.631670939743065 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9869 -0.7538  0.0300  0.8609  3.5396 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95497    0.08989 110.745  < 2e-16 ***
## category_code_LT01_1_count   0.23868    0.08897   2.683  0.00755 ** 
## category_code_LT01_4_count   0.70401    0.09425   7.470 3.71e-13 ***
## category_code_LT01_5_count   0.93350    0.06119  15.257  < 2e-16 ***
## category_code_LT01_7_count   0.34787    0.15737   2.211  0.02753 *  
## category_code_LT01_10_count  0.13380    0.11086   1.207  0.22804    
## category_code_LT01_11_count  0.33879    0.11384   2.976  0.00306 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6361, Adjusted R-squared:  0.6317 
## F-statistic: 143.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 0.625197502054002 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9831 -0.7603  0.0096  0.8688  3.7387 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94649    0.09063 109.747  < 2e-16 ***
## category_code_LT01_1_count   0.27905    0.08915   3.130  0.00185 ** 
## category_code_LT01_4_count   0.83078    0.08464   9.815  < 2e-16 ***
## category_code_LT01_5_count   0.94026    0.06199  15.167  < 2e-16 ***
## category_code_LT01_7_count   0.46056    0.15407   2.989  0.00294 ** 
## category_code_LT01_10_count  0.14864    0.11183   1.329  0.18440    
## category_code_LT01_12_count  0.09704    0.20543   0.472  0.63688    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6297, Adjusted R-squared:  0.6252 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 0.625084806821723 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9849 -0.7599  0.0390  0.8603  3.7295 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94576    0.09065 109.714  < 2e-16 ***
## category_code_LT01_1_count   0.28773    0.08917   3.227  0.00134 ** 
## category_code_LT01_4_count   0.83705    0.08391   9.976  < 2e-16 ***
## category_code_LT01_5_count   0.94392    0.06166  15.307  < 2e-16 ***
## category_code_LT01_7_count   0.46509    0.15495   3.001  0.00282 ** 
## category_code_LT01_10_count  0.15217    0.11172   1.362  0.17379    
## category_code_LT01_13_count -0.06759    0.24605  -0.275  0.78365    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6296, Adjusted R-squared:  0.6251 
## F-statistic: 139.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 0.625147230179541 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9827 -0.7522  0.0185  0.8950  3.7231 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94212    0.09119 109.022  < 2e-16 ***
## category_code_LT01_1_count   0.28810    0.08885   3.242  0.00127 ** 
## category_code_LT01_4_count   0.83942    0.08423   9.966  < 2e-16 ***
## category_code_LT01_5_count   0.94602    0.06198  15.264  < 2e-16 ***
## category_code_LT01_7_count   0.46326    0.15423   3.004  0.00280 ** 
## category_code_LT01_10_count  0.16107    0.11428   1.409  0.15937    
## category_code_LT01_14_count -0.13320    0.33589  -0.397  0.69188    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6297, Adjusted R-squared:  0.6251 
## F-statistic: 139.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 0.625049626155829 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -5.984 -0.765  0.027  0.862  3.729 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94546    0.09073 109.617  < 2e-16 ***
## category_code_LT01_1_count   0.28735    0.08993   3.195  0.00149 ** 
## category_code_LT01_4_count   0.83708    0.08400   9.965  < 2e-16 ***
## category_code_LT01_5_count   0.94343    0.06164  15.305  < 2e-16 ***
## category_code_LT01_7_count   0.45927    0.15430   2.976  0.00306 ** 
## category_code_LT01_10_count  0.15319    0.11216   1.366  0.17261    
## category_code_LT01_15_count -0.13050    0.76121  -0.171  0.86395    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6296, Adjusted R-squared:  0.625 
## F-statistic: 139.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 0.625885531472488 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9848 -0.7623  0.0340  0.8708  3.7368 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94725    0.09055 109.853  < 2e-16 ***
## category_code_LT01_1_count   0.28573    0.08832   3.235  0.00130 ** 
## category_code_LT01_4_count   0.83131    0.08390   9.909  < 2e-16 ***
## category_code_LT01_5_count   0.94155    0.06160  15.285  < 2e-16 ***
## category_code_LT01_7_count   0.46055    0.15393   2.992  0.00291 ** 
## category_code_LT01_10_count  0.14547    0.11171   1.302  0.19343    
## category_code_LT01_16_count  1.22887    1.15781   1.061  0.28904    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6304, Adjusted R-squared:  0.6259 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 0.630628158626215 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0188 -0.7733  0.0266  0.8460  3.6464 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98520    0.08652 115.407  < 2e-16 ***
## category_code_LT01_1_count   0.23784    0.08939   2.661  0.00805 ** 
## category_code_LT01_4_count   0.71526    0.09393   7.615 1.36e-13 ***
## category_code_LT01_5_count   0.93588    0.06156  15.202  < 2e-16 ***
## category_code_LT01_7_count   0.35929    0.15746   2.282  0.02293 *  
## category_code_LT01_11_count  0.35409    0.11796   3.002  0.00282 ** 
## category_code_LT01_12_count -0.05437    0.21101  -0.258  0.79677    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6351, Adjusted R-squared:  0.6306 
## F-statistic: 142.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 0.630632267207499 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0176 -0.7743  0.0265  0.8613  3.6514 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98474    0.08652 115.406  < 2e-16 ***
## category_code_LT01_1_count   0.23892    0.08979   2.661  0.00805 ** 
## category_code_LT01_4_count   0.71593    0.09397   7.619 1.33e-13 ***
## category_code_LT01_5_count   0.93480    0.06129  15.251  < 2e-16 ***
## category_code_LT01_7_count   0.36610    0.15800   2.317  0.02091 *  
## category_code_LT01_11_count  0.34638    0.11384   3.043  0.00247 ** 
## category_code_LT01_13_count -0.06545    0.24416  -0.268  0.78877    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6351, Adjusted R-squared:  0.6306 
## F-statistic: 142.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 0.630582830282254 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0174 -0.7705  0.0299  0.8489  3.6535 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98458    0.08664 115.242  < 2e-16 ***
## category_code_LT01_1_count   0.23653    0.08947   2.644  0.00847 ** 
## category_code_LT01_4_count   0.71601    0.09452   7.575  1.8e-13 ***
## category_code_LT01_5_count   0.93484    0.06162  15.171  < 2e-16 ***
## category_code_LT01_7_count   0.36252    0.15747   2.302  0.02174 *  
## category_code_LT01_11_count  0.34607    0.11385   3.040  0.00249 ** 
## category_code_LT01_14_count -0.02553    0.32585  -0.078  0.93758    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.635,  Adjusted R-squared:  0.6306 
## F-statistic: 142.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 0.63060452409241 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0171 -0.7742  0.0272  0.8466  3.6511 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98465    0.08653 115.387  < 2e-16 ***
## category_code_LT01_1_count   0.23875    0.09039   2.641  0.00852 ** 
## category_code_LT01_4_count   0.71589    0.09401   7.615 1.36e-13 ***
## category_code_LT01_5_count   0.93431    0.06127  15.249  < 2e-16 ***
## category_code_LT01_7_count   0.36021    0.15739   2.289  0.02253 *  
## category_code_LT01_11_count  0.34711    0.11396   3.046  0.00245 ** 
## category_code_LT01_15_count -0.14086    0.75320  -0.187  0.85173    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6351, Adjusted R-squared:  0.6306 
## F-statistic: 142.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 0.631331607304498 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0160 -0.7633  0.0432  0.8406  3.6560 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98467    0.08643 115.518  < 2e-16 ***
## category_code_LT01_1_count   0.23775    0.08900   2.671  0.00780 ** 
## category_code_LT01_4_count   0.71199    0.09389   7.583  1.7e-13 ***
## category_code_LT01_5_count   0.93268    0.06123  15.232  < 2e-16 ***
## category_code_LT01_7_count   0.36274    0.15702   2.310  0.02129 *  
## category_code_LT01_11_count  0.34104    0.11384   2.996  0.00288 ** 
## category_code_LT01_16_count  1.15099    1.14904   1.002  0.31699    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6358, Adjusted R-squared:  0.6313 
## F-statistic: 142.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 0.623895955974716 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0168 -0.7690  0.0186  0.8642  3.8690 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97944    0.08729 114.325  < 2e-16 ***
## category_code_LT01_1_count   0.27906    0.09001   3.100  0.00205 ** 
## category_code_LT01_4_count   0.84631    0.08411  10.062  < 2e-16 ***
## category_code_LT01_5_count   0.94137    0.06212  15.153  < 2e-16 ***
## category_code_LT01_7_count   0.48282    0.15463   3.122  0.00190 ** 
## category_code_LT01_12_count  0.11208    0.20551   0.545  0.58575    
## category_code_LT01_13_count -0.06109    0.24638  -0.248  0.80428    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6284, Adjusted R-squared:  0.6239 
## F-statistic: 138.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 0.623862596379129 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0167 -0.7686  0.0133  0.8656  3.8707 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97901    0.08741 114.160  < 2e-16 ***
## category_code_LT01_1_count   0.27725    0.08962   3.094  0.00209 ** 
## category_code_LT01_4_count   0.84683    0.08460  10.010  < 2e-16 ***
## category_code_LT01_5_count   0.94177    0.06241  15.091  < 2e-16 ***
## category_code_LT01_7_count   0.47996    0.15403   3.116  0.00194 ** 
## category_code_LT01_12_count  0.11326    0.20592   0.550  0.58255    
## category_code_LT01_14_count -0.04411    0.32945  -0.134  0.89355    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6284, Adjusted R-squared:  0.6239 
## F-statistic: 138.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 0.623849440730674 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0167 -0.7691  0.0146  0.8685  3.8705 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97958    0.08731 114.305  < 2e-16 ***
## category_code_LT01_1_count   0.27667    0.09083   3.046  0.00244 ** 
## category_code_LT01_4_count   0.84573    0.08430  10.032  < 2e-16 ***
## category_code_LT01_5_count   0.94096    0.06210  15.151  < 2e-16 ***
## category_code_LT01_7_count   0.47852    0.15388   3.110  0.00198 ** 
## category_code_LT01_12_count  0.11131    0.20565   0.541  0.58857    
## category_code_LT01_15_count -0.02084    0.75976  -0.027  0.97813    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6284, Adjusted R-squared:  0.6238 
## F-statistic: 138.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 0.624815791609424 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0151 -0.7690  0.0242  0.8728  3.8700 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97941    0.08718 114.469  < 2e-16 ***
## category_code_LT01_1_count   0.27761    0.08918   3.113  0.00196 ** 
## category_code_LT01_4_count   0.83970    0.08411   9.983  < 2e-16 ***
## category_code_LT01_5_count   0.93893    0.06205  15.132  < 2e-16 ***
## category_code_LT01_7_count   0.47786    0.15355   3.112  0.00197 ** 
## category_code_LT01_12_count  0.11075    0.20525   0.540  0.58974    
## category_code_LT01_16_count  1.30264    1.15800   1.125  0.26118    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 0.62367653008688 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0197 -0.7688  0.0126  0.8686  3.8643 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97926    0.08743 114.134  < 2e-16 ***
## category_code_LT01_1_count   0.28618    0.08974   3.189  0.00152 ** 
## category_code_LT01_4_count   0.85404    0.08390  10.180  < 2e-16 ***
## category_code_LT01_5_count   0.94574    0.06213  15.222  < 2e-16 ***
## category_code_LT01_7_count   0.48422    0.15498   3.124  0.00189 ** 
## category_code_LT01_13_count -0.06018    0.24650  -0.244  0.80721    
## category_code_LT01_14_count -0.03443    0.32895  -0.105  0.91669    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6237 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 0.62367168152278 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0196 -0.7692  0.0143  0.8686  3.8637 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97963    0.08733 114.274  < 2e-16 ***
## category_code_LT01_1_count   0.28645    0.09098   3.148  0.00174 ** 
## category_code_LT01_4_count   0.85337    0.08348  10.222  < 2e-16 ***
## category_code_LT01_5_count   0.94506    0.06178  15.298  < 2e-16 ***
## category_code_LT01_7_count   0.48284    0.15476   3.120  0.00192 ** 
## category_code_LT01_13_count -0.06104    0.24733  -0.247  0.80518    
## category_code_LT01_15_count -0.05184    0.76219  -0.068  0.94580    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6237 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 0.624625730764346 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0180 -0.7691  0.0204  0.8594  3.8639 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97955    0.08720 114.440  < 2e-16 ***
## category_code_LT01_1_count   0.28620    0.08921   3.208  0.00142 ** 
## category_code_LT01_4_count   0.84697    0.08331  10.166  < 2e-16 ***
## category_code_LT01_5_count   0.94295    0.06173  15.277  < 2e-16 ***
## category_code_LT01_7_count   0.48175    0.15448   3.118  0.00192 ** 
## category_code_LT01_13_count -0.05070    0.24625  -0.206  0.83697    
## category_code_LT01_16_count  1.29701    1.15889   1.119  0.26361    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6292, Adjusted R-squared:  0.6246 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 0.623632578245055 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0195 -0.7690  0.0150  0.8687  3.8656 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97939    0.08745 114.115  < 2e-16 ***
## category_code_LT01_1_count   0.28408    0.09045   3.141  0.00179 ** 
## category_code_LT01_4_count   0.85349    0.08404  10.156  < 2e-16 ***
## category_code_LT01_5_count   0.94527    0.06210  15.221  < 2e-16 ***
## category_code_LT01_7_count   0.47979    0.15421   3.111  0.00197 ** 
## category_code_LT01_14_count -0.03269    0.32889  -0.099  0.92087    
## category_code_LT01_15_count -0.03616    0.75948  -0.048  0.96204    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6236 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 0.624594951244652 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0179 -0.7691  0.0205  0.8610  3.8654 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97950    0.08732 114.282  < 2e-16 ***
## category_code_LT01_1_count   0.28421    0.08886   3.199  0.00147 ** 
## category_code_LT01_4_count   0.84676    0.08392  10.090  < 2e-16 ***
## category_code_LT01_5_count   0.94287    0.06206  15.193  < 2e-16 ***
## category_code_LT01_7_count   0.47876    0.15388   3.111  0.00197 ** 
## category_code_LT01_14_count -0.01517    0.32884  -0.046  0.96323    
## category_code_LT01_16_count  1.30219    1.15963   1.123  0.26201    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6246 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 0.624593613229289 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0179 -0.7692  0.0208  0.8615  3.8653 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97967    0.08722 114.421  < 2e-16 ***
## category_code_LT01_1_count   0.28414    0.08993   3.159  0.00168 ** 
## category_code_LT01_4_count   0.84639    0.08347  10.140  < 2e-16 ***
## category_code_LT01_5_count   0.94257    0.06170  15.277  < 2e-16 ***
## category_code_LT01_7_count   0.47819    0.15373   3.111  0.00198 ** 
## category_code_LT01_15_count -0.01474    0.75874  -0.019  0.98451    
## category_code_LT01_16_count  1.30416    1.15869   1.126  0.26091    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6246 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 0.621744753857529 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9843 -0.7768  0.0121  0.8834  3.7253 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94018    0.09103 109.202  < 2e-16 ***
## category_code_LT01_1_count   0.30127    0.08858   3.401 0.000725 ***
## category_code_LT01_4_count   0.89356    0.08043  11.110  < 2e-16 ***
## category_code_LT01_5_count   0.95111    0.06271  15.166  < 2e-16 ***
## category_code_LT01_8_count  -0.18628    0.27447  -0.679 0.497650    
## category_code_LT01_9_count   0.46396    0.22605   2.052 0.040658 *  
## category_code_LT01_10_count  0.15251    0.11273   1.353 0.176742    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6263, Adjusted R-squared:  0.6217 
## F-statistic: 137.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 0.629587399726466 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0148 -0.7699  0.0504  0.9090  3.6250 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98030    0.08672 115.084  < 2e-16 ***
## category_code_LT01_1_count   0.24096    0.08920   2.701 0.007149 ** 
## category_code_LT01_4_count   0.73626    0.09304   7.914 1.68e-14 ***
## category_code_LT01_5_count   0.93727    0.06219  15.070  < 2e-16 ***
## category_code_LT01_8_count  -0.15098    0.27168  -0.556 0.578640    
## category_code_LT01_9_count   0.43030    0.22278   1.932 0.053991 .  
## category_code_LT01_11_count  0.38887    0.11104   3.502 0.000504 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6341, Adjusted R-squared:  0.6296 
## F-statistic: 141.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 0.620561903931516 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0154 -0.7853  0.0245  0.9207  3.8654 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97335    0.08775 113.655  < 2e-16 ***
## category_code_LT01_1_count   0.29301    0.08944   3.276  0.00113 ** 
## category_code_LT01_4_count   0.90391    0.08050  11.229  < 2e-16 ***
## category_code_LT01_5_count   0.94811    0.06314  15.017  < 2e-16 ***
## category_code_LT01_8_count  -0.18392    0.27500  -0.669  0.50394    
## category_code_LT01_9_count   0.50194    0.22450   2.236  0.02581 *  
## category_code_LT01_12_count  0.11194    0.20654   0.542  0.58809    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6251, Adjusted R-squared:  0.6206 
## F-statistic: 136.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 0.620366466120934 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0177 -0.7884  0.0254  0.9086  3.8626 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97368    0.08777 113.629  < 2e-16 ***
## category_code_LT01_1_count   0.29658    0.08968   3.307  0.00101 ** 
## category_code_LT01_4_count   0.90902    0.07993  11.373  < 2e-16 ***
## category_code_LT01_5_count   0.95095    0.06291  15.116  < 2e-16 ***
## category_code_LT01_8_count  -0.17568    0.27543  -0.638  0.52387    
## category_code_LT01_9_count   0.50677    0.22499   2.252  0.02474 *  
## category_code_LT01_13_count  0.04991    0.24708   0.202  0.83999    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6249, Adjusted R-squared:  0.6204 
## F-statistic: 136.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 0.620336391520324 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0180 -0.7899  0.0238  0.9054  3.8608 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97337    0.08791 113.451  < 2e-16 ***
## category_code_LT01_1_count   0.29960    0.08915   3.361 0.000838 ***
## category_code_LT01_4_count   0.91100    0.08038  11.334  < 2e-16 ***
## category_code_LT01_5_count   0.95187    0.06316  15.071  < 2e-16 ***
## category_code_LT01_8_count  -0.17895    0.27495  -0.651 0.515435    
## category_code_LT01_9_count   0.50448    0.22498   2.242 0.025389 *  
## category_code_LT01_14_count -0.01445    0.33039  -0.044 0.965137    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6249, Adjusted R-squared:  0.6203 
## F-statistic: 136.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 0.620345693682142 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0179 -0.7888  0.0267  0.9060  3.8598 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97340    0.08779 113.607  < 2e-16 ***
## category_code_LT01_1_count   0.30112    0.09017   3.339 0.000904 ***
## category_code_LT01_4_count   0.91111    0.07975  11.424  < 2e-16 ***
## category_code_LT01_5_count   0.95158    0.06283  15.146  < 2e-16 ***
## category_code_LT01_8_count  -0.17885    0.27494  -0.651 0.515660    
## category_code_LT01_9_count   0.50316    0.22461   2.240 0.025528 *  
## category_code_LT01_15_count -0.09002    0.76236  -0.118 0.906053    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6249, Adjusted R-squared:  0.6203 
## F-statistic: 136.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 0.621208868339909 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0173 -0.7878  0.0262  0.9019  3.8597 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97365    0.08768 113.756  < 2e-16 ***
## category_code_LT01_1_count   0.30088    0.08864   3.394 0.000743 ***
## category_code_LT01_4_count   0.90550    0.07964  11.370  < 2e-16 ***
## category_code_LT01_5_count   0.95039    0.06277  15.141  < 2e-16 ***
## category_code_LT01_8_count  -0.19345    0.27495  -0.704 0.482026    
## category_code_LT01_9_count   0.49277    0.22452   2.195 0.028646 *  
## category_code_LT01_16_count  1.24133    1.16628   1.064 0.287692    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6258, Adjusted R-squared:  0.6212 
## F-statistic: 136.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 0.628212337155298 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9920 -0.7590  0.0425  0.8957  3.4723 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95185    0.09031 110.196  < 2e-16 ***
## category_code_LT01_1_count   0.25061    0.08933   2.806 0.005222 ** 
## category_code_LT01_4_count   0.74100    0.09327   7.945 1.34e-14 ***
## category_code_LT01_5_count   0.94537    0.06214  15.214  < 2e-16 ***
## category_code_LT01_8_count  -0.14233    0.27211  -0.523 0.601161    
## category_code_LT01_10_count  0.15321    0.11112   1.379 0.168583    
## category_code_LT01_11_count  0.39774    0.11105   3.581 0.000376 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 491 degrees of freedom
## Multiple R-squared:  0.6327, Adjusted R-squared:  0.6282 
## F-statistic:   141 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 0.618686718627468 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9889 -0.7743  0.0348  0.9068  3.6921 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93979    0.09140 108.756  < 2e-16 ***
## category_code_LT01_1_count   0.30645    0.08953   3.423 0.000672 ***
## category_code_LT01_4_count   0.91468    0.08053  11.358  < 2e-16 ***
## category_code_LT01_5_count   0.95830    0.06310  15.188  < 2e-16 ***
## category_code_LT01_8_count  -0.17411    0.27560  -0.632 0.527848    
## category_code_LT01_10_count  0.17979    0.11238   1.600 0.110254    
## category_code_LT01_12_count  0.10176    0.20731   0.491 0.623734    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6233, Adjusted R-squared:  0.6187 
## F-statistic: 135.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 0.618499589715053 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9907 -0.7709  0.0301  0.9005  3.6854 
## 
## Coefficients:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.9393795  0.0914267 108.714  < 2e-16 ***
## category_code_LT01_1_count   0.3121369  0.0897125   3.479 0.000547 ***
## category_code_LT01_4_count   0.9204194  0.0799130  11.518  < 2e-16 ***
## category_code_LT01_5_count   0.9614665  0.0628420  15.300  < 2e-16 ***
## category_code_LT01_8_count  -0.1697787  0.2760904  -0.615 0.538880    
## category_code_LT01_10_count  0.1826904  0.1123155   1.627 0.104467    
## category_code_LT01_13_count  0.0003028  0.2473249   0.001 0.999024    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6231, Adjusted R-squared:  0.6185 
## F-statistic: 135.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 0.618552457712708 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9892 -0.7755  0.0239  0.8923  3.6793 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93669    0.09199 108.024  < 2e-16 ***
## category_code_LT01_1_count   0.31461    0.08929   3.524 0.000466 ***
## category_code_LT01_4_count   0.92285    0.08023  11.503  < 2e-16 ***
## category_code_LT01_5_count   0.96321    0.06313  15.258  < 2e-16 ***
## category_code_LT01_8_count  -0.16933    0.27552  -0.615 0.539118    
## category_code_LT01_10_count  0.18919    0.11497   1.646 0.100487    
## category_code_LT01_14_count -0.08831    0.33853  -0.261 0.794302    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6232, Adjusted R-squared:  0.6186 
## F-statistic: 135.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 0.618578477038816 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9894 -0.7703  0.0250  0.8946  3.6797 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93817    0.09148 108.633  < 2e-16 ***
## category_code_LT01_1_count   0.31729    0.09024   3.516 0.000478 ***
## category_code_LT01_4_count   0.92152    0.07976  11.554  < 2e-16 ***
## category_code_LT01_5_count   0.96138    0.06277  15.315  < 2e-16 ***
## category_code_LT01_8_count  -0.16947    0.27550  -0.615 0.538767    
## category_code_LT01_10_count  0.18581    0.11266   1.649 0.099733 .  
## category_code_LT01_15_count -0.24434    0.76675  -0.319 0.750110    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6232, Adjusted R-squared:  0.6186 
## F-statistic: 135.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 0.619412786215699 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9910 -0.7677  0.0352  0.9082  3.6898 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94064    0.09131 108.864  < 2e-16 ***
## category_code_LT01_1_count   0.31354    0.08870   3.535 0.000446 ***
## category_code_LT01_4_count   0.91533    0.07974  11.479  < 2e-16 ***
## category_code_LT01_5_count   0.96004    0.06272  15.307  < 2e-16 ***
## category_code_LT01_8_count  -0.18460    0.27554  -0.670 0.503195    
## category_code_LT01_10_count  0.17667    0.11225   1.574 0.116151    
## category_code_LT01_16_count  1.26908    1.16921   1.085 0.278270    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.624,  Adjusted R-squared:  0.6194 
## F-statistic: 135.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 0.626880034664854 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0286 -0.7698  0.0290  0.8885  3.5906 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98642    0.08699 114.798  < 2e-16 ***
## category_code_LT01_1_count   0.25046    0.08976   2.790 0.005469 ** 
## category_code_LT01_4_count   0.75515    0.09285   8.133 3.44e-15 ***
## category_code_LT01_5_count   0.94835    0.06248  15.178  < 2e-16 ***
## category_code_LT01_8_count  -0.12856    0.27274  -0.471 0.637601    
## category_code_LT01_11_count  0.42014    0.11478   3.660 0.000279 ***
## category_code_LT01_12_count -0.07958    0.21187  -0.376 0.707361    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6314, Adjusted R-squared:  0.6269 
## F-statistic: 140.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 0.626775663611165 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0270 -0.7663  0.0248  0.8990  3.5999 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98604    0.08700 114.781  < 2e-16 ***
## category_code_LT01_1_count   0.24846    0.09028   2.752 0.006143 ** 
## category_code_LT01_4_count   0.75575    0.09298   8.128 3.57e-15 ***
## category_code_LT01_5_count   0.94646    0.06231  15.189  < 2e-16 ***
## category_code_LT01_8_count  -0.13381    0.27307  -0.490 0.624343    
## category_code_LT01_11_count  0.40931    0.11102   3.687 0.000252 ***
## category_code_LT01_13_count -0.01497    0.24461  -0.061 0.951227    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 0.626776302682068 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0269 -0.7666  0.0276  0.9019  3.6007 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98639    0.08712 114.629  < 2e-16 ***
## category_code_LT01_1_count   0.24713    0.08990   2.749 0.006201 ** 
## category_code_LT01_4_count   0.75467    0.09358   8.064 5.67e-15 ***
## category_code_LT01_5_count   0.94585    0.06261  15.108  < 2e-16 ***
## category_code_LT01_8_count  -0.13299    0.27256  -0.488 0.625825    
## category_code_LT01_11_count  0.40902    0.11097   3.686 0.000253 ***
## category_code_LT01_14_count  0.02214    0.32693   0.068 0.946037    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 0.626842898768366 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0263 -0.7659  0.0244  0.8947  3.5970 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98561    0.08700 114.771  < 2e-16 ***
## category_code_LT01_1_count   0.25235    0.09075   2.781 0.005635 ** 
## category_code_LT01_4_count   0.75634    0.09289   8.142 3.23e-15 ***
## category_code_LT01_5_count   0.94620    0.06225  15.200  < 2e-16 ***
## category_code_LT01_8_count  -0.13222    0.27253  -0.485 0.627787    
## category_code_LT01_11_count  0.41023    0.11102   3.695 0.000244 ***
## category_code_LT01_15_count -0.22957    0.75598  -0.304 0.761510    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 0.627544987236861 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0259 -0.7660  0.0338  0.8938  3.6028 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98593    0.08691 114.901  < 2e-16 ***
## category_code_LT01_1_count   0.24983    0.08941   2.794 0.005403 ** 
## category_code_LT01_4_count   0.75243    0.09281   8.107 4.16e-15 ***
## category_code_LT01_5_count   0.94515    0.06220  15.195  < 2e-16 ***
## category_code_LT01_8_count  -0.14703    0.27263  -0.539 0.589917    
## category_code_LT01_11_count  0.40395    0.11097   3.640 0.000301 ***
## category_code_LT01_16_count  1.16679    1.15646   1.009 0.313506    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.632,  Adjusted R-squared:  0.6275 
## F-statistic: 140.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 0.616700677825279 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0295 -0.7693  0.0116  0.9289  3.8517 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97976    0.08815 113.210  < 2e-16 ***
## category_code_LT01_1_count   0.30351    0.09064   3.349 0.000875 ***
## category_code_LT01_4_count   0.93641    0.07979  11.735  < 2e-16 ***
## category_code_LT01_5_count   0.95925    0.06332  15.150  < 2e-16 ***
## category_code_LT01_8_count  -0.16365    0.27681  -0.591 0.554649    
## category_code_LT01_12_count  0.11906    0.20758   0.574 0.566524    
## category_code_LT01_13_count  0.01231    0.24778   0.050 0.960386    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6167 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 0.616701672571171 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0296 -0.7696  0.0128  0.9288  3.8514 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98001    0.08828 113.055  < 2e-16 ***
## category_code_LT01_1_count   0.30363    0.09014   3.369 0.000815 ***
## category_code_LT01_4_count   0.93603    0.08037  11.647  < 2e-16 ***
## category_code_LT01_5_count   0.95900    0.06357  15.084  < 2e-16 ***
## category_code_LT01_8_count  -0.16468    0.27627  -0.596 0.551386    
## category_code_LT01_12_count  0.11840    0.20798   0.569 0.569426    
## category_code_LT01_14_count  0.02031    0.33197   0.061 0.951236    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6167 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 0.616717472794928 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0294 -0.7690  0.0113  0.9290  3.8498 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97948    0.08816 113.193  < 2e-16 ***
## category_code_LT01_1_count   0.30669    0.09125   3.361 0.000837 ***
## category_code_LT01_4_count   0.93752    0.07971  11.761  < 2e-16 ***
## category_code_LT01_5_count   0.95940    0.06325  15.167  < 2e-16 ***
## category_code_LT01_8_count  -0.16422    0.27626  -0.594 0.552484    
## category_code_LT01_12_count  0.11802    0.20770   0.568 0.570161    
## category_code_LT01_15_count -0.11867    0.76625  -0.155 0.876988    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6167 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 0.617748360092492 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0284 -0.7692  0.0178  0.9315  3.8503 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97965    0.08803 113.367  < 2e-16 ***
## category_code_LT01_1_count   0.30570    0.08964   3.410 0.000702 ***
## category_code_LT01_4_count   0.93046    0.07962  11.686  < 2e-16 ***
## category_code_LT01_5_count   0.95781    0.06318  15.159  < 2e-16 ***
## category_code_LT01_8_count  -0.18072    0.27623  -0.654 0.513254    
## category_code_LT01_12_count  0.11880    0.20728   0.573 0.566821    
## category_code_LT01_16_count  1.35891    1.17034   1.161 0.246154    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6224, Adjusted R-squared:  0.6177 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616451397383926 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0324 -0.7647 -0.0049  0.9173  3.8471 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98049    0.08830 113.024  < 2e-16 ***
## category_code_LT01_1_count   0.30915    0.09042   3.419  0.00068 ***
## category_code_LT01_4_count   0.94232    0.07981  11.808  < 2e-16 ***
## category_code_LT01_5_count   0.96230    0.06337  15.185  < 2e-16 ***
## category_code_LT01_8_count  -0.15856    0.27676  -0.573  0.56695    
## category_code_LT01_13_count  0.01462    0.24787   0.059  0.95298    
## category_code_LT01_14_count  0.03256    0.33145   0.098  0.92180    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6165 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616466835185189 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0321 -0.7601  0.0021  0.9180  3.8452 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97974    0.08819 113.156  < 2e-16 ***
## category_code_LT01_1_count   0.31301    0.09158   3.418 0.000683 ***
## category_code_LT01_4_count   0.94443    0.07903  11.951  < 2e-16 ***
## category_code_LT01_5_count   0.96298    0.06300  15.285  < 2e-16 ***
## category_code_LT01_8_count  -0.15827    0.27673  -0.572 0.567647    
## category_code_LT01_13_count  0.01047    0.24882   0.042 0.966458    
## category_code_LT01_15_count -0.13188    0.76902  -0.171 0.863903    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6165 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617499057058243 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0312 -0.7628  0.0026  0.9186  3.8462 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97997    0.08806 113.332  < 2e-16 ***
## category_code_LT01_1_count   0.31117    0.08983   3.464 0.000578 ***
## category_code_LT01_4_count   0.93700    0.07894  11.869  < 2e-16 ***
## category_code_LT01_5_count   0.96128    0.06293  15.274  < 2e-16 ***
## category_code_LT01_8_count  -0.17397    0.27669  -0.629 0.529799    
## category_code_LT01_13_count  0.02248    0.24760   0.091 0.927707    
## category_code_LT01_16_count  1.36307    1.17119   1.164 0.245057    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6175 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 0.61647267930466 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0322 -0.7656  0.0026  0.9258  3.8450 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98016    0.08831 113.008  < 2e-16 ***
## category_code_LT01_1_count   0.31273    0.09092   3.440 0.000632 ***
## category_code_LT01_4_count   0.94354    0.07967  11.843  < 2e-16 ***
## category_code_LT01_5_count   0.96245    0.06330  15.205  < 2e-16 ***
## category_code_LT01_8_count  -0.15930    0.27621  -0.577 0.564380    
## category_code_LT01_14_count  0.03188    0.33141   0.096 0.923411    
## category_code_LT01_15_count -0.13427    0.76599  -0.175 0.860926    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6165 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617510847594489 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0313 -0.7662  0.0058  0.9270  3.8457 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98063    0.08818 113.186  < 2e-16 ***
## category_code_LT01_1_count   0.31096    0.08937   3.480 0.000547 ***
## category_code_LT01_4_count   0.93570    0.07965  11.748  < 2e-16 ***
## category_code_LT01_5_count   0.96050    0.06324  15.189  < 2e-16 ***
## category_code_LT01_8_count  -0.17610    0.27619  -0.638 0.524036    
## category_code_LT01_14_count  0.05066    0.33133   0.153 0.878546    
## category_code_LT01_16_count  1.36856    1.17202   1.168 0.243498    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6175 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617509443115048 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0310 -0.7627  0.0061  0.9271  3.8441 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97968    0.08807 113.314  < 2e-16 ***
## category_code_LT01_1_count   0.31468    0.09034   3.483  0.00054 ***
## category_code_LT01_4_count   0.93831    0.07881  11.905  < 2e-16 ***
## category_code_LT01_5_count   0.96152    0.06287  15.295  < 2e-16 ***
## category_code_LT01_8_count  -0.17522    0.27617  -0.634  0.52607    
## category_code_LT01_15_count -0.11239    0.76518  -0.147  0.88329    
## category_code_LT01_16_count  1.35570    1.17107   1.158  0.24757    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6175 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.630331257085271 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9817 -0.7522  0.0313  0.9366  3.5180 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95100    0.09004 110.523  < 2e-16 ***
## category_code_LT01_1_count   0.24204    0.08909   2.717 0.006827 ** 
## category_code_LT01_4_count   0.72480    0.09340   7.760 4.95e-14 ***
## category_code_LT01_5_count   0.93171    0.06142  15.170  < 2e-16 ***
## category_code_LT01_9_count   0.39405    0.22418   1.758 0.079419 .  
## category_code_LT01_10_count  0.12717    0.11164   1.139 0.255231    
## category_code_LT01_11_count  0.38284    0.11109   3.446 0.000617 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6348, Adjusted R-squared:  0.6303 
## F-statistic: 142.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 0.621547851095603 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9769 -0.7657  0.0202  0.9071  3.7357 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93927    0.09103 109.183  < 2e-16 ***
## category_code_LT01_1_count   0.29419    0.08931   3.294  0.00106 ** 
## category_code_LT01_4_count   0.88847    0.08127  10.932  < 2e-16 ***
## category_code_LT01_5_count   0.94172    0.06238  15.096  < 2e-16 ***
## category_code_LT01_9_count   0.45845    0.22603   2.028  0.04307 *  
## category_code_LT01_10_count  0.14838    0.11289   1.314  0.18933    
## category_code_LT01_12_count  0.09345    0.20644   0.453  0.65097    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6261, Adjusted R-squared:  0.6215 
## F-statistic:   137 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 0.621416340403924 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9786 -0.7694  0.0163  0.8984  3.7318 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93922    0.09106 109.149  < 2e-16 ***
## category_code_LT01_1_count   0.29704    0.08952   3.318 0.000973 ***
## category_code_LT01_4_count   0.89243    0.08075  11.052  < 2e-16 ***
## category_code_LT01_5_count   0.94427    0.06209  15.208  < 2e-16 ***
## category_code_LT01_9_count   0.46244    0.22662   2.041 0.041828 *  
## category_code_LT01_10_count  0.15014    0.11286   1.330 0.184049    
## category_code_LT01_13_count  0.04565    0.24650   0.185 0.853155    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.626,  Adjusted R-squared:  0.6214 
## F-statistic:   137 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 0.621478819780439 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9767 -0.7761  0.0117  0.9106  3.7217 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93544    0.09161 108.451  < 2e-16 ***
## category_code_LT01_1_count   0.30257    0.08904   3.398 0.000734 ***
## category_code_LT01_4_count   0.89668    0.08093  11.080  < 2e-16 ***
## category_code_LT01_5_count   0.94696    0.06237  15.182  < 2e-16 ***
## category_code_LT01_9_count   0.46224    0.22618   2.044 0.041520 *  
## category_code_LT01_10_count  0.15927    0.11534   1.381 0.167946    
## category_code_LT01_14_count -0.11460    0.33744  -0.340 0.734282    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.626,  Adjusted R-squared:  0.6215 
## F-statistic:   137 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 0.62143635876956 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9777 -0.7697  0.0215  0.8938  3.7249 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93799    0.09112 109.062  < 2e-16 ***
## category_code_LT01_1_count   0.30344    0.09005   3.369 0.000812 ***
## category_code_LT01_4_count   0.89466    0.08055  11.106  < 2e-16 ***
## category_code_LT01_5_count   0.94473    0.06203  15.230  < 2e-16 ***
## category_code_LT01_9_count   0.45736    0.22621   2.022 0.043733 *  
## category_code_LT01_10_count  0.15355    0.11323   1.356 0.175692    
## category_code_LT01_15_count -0.18765    0.76441  -0.245 0.806185    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.626,  Adjusted R-squared:  0.6214 
## F-statistic:   137 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 0.622118998536965 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9786 -0.7675  0.0232  0.8825  3.7329 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93994    0.09097 109.269  < 2e-16 ***
## category_code_LT01_1_count   0.30076    0.08850   3.398 0.000733 ***
## category_code_LT01_4_count   0.88966    0.08049  11.053  < 2e-16 ***
## category_code_LT01_5_count   0.94322    0.06200  15.214  < 2e-16 ***
## category_code_LT01_9_count   0.45029    0.22604   1.992 0.046916 *  
## category_code_LT01_10_count  0.14611    0.11277   1.296 0.195693    
## category_code_LT01_16_count  1.13357    1.16463   0.973 0.330872    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6267, Adjusted R-squared:  0.6221 
## F-statistic: 137.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.629464950624145 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0119 -0.7694  0.0536  0.9009  3.6161 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97944    0.08671 115.086  < 2e-16 ***
## category_code_LT01_1_count   0.24206    0.08947   2.705 0.007060 ** 
## category_code_LT01_4_count   0.73517    0.09304   7.901 1.83e-14 ***
## category_code_LT01_5_count   0.93428    0.06177  15.126  < 2e-16 ***
## category_code_LT01_9_count   0.42538    0.22269   1.910 0.056684 .  
## category_code_LT01_11_count  0.40188    0.11480   3.501 0.000506 ***
## category_code_LT01_12_count -0.08074    0.21096  -0.383 0.702080    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6339, Adjusted R-squared:  0.6295 
## F-statistic: 141.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.629362265500935 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0098 -0.7687  0.0481  0.9147  3.6273 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97909    0.08672 115.072  < 2e-16 ***
## category_code_LT01_1_count   0.23798    0.08999   2.644 0.008443 ** 
## category_code_LT01_4_count   0.73488    0.09320   7.885 2.06e-14 ***
## category_code_LT01_5_count   0.93179    0.06154  15.140  < 2e-16 ***
## category_code_LT01_9_count   0.42759    0.22325   1.915 0.056035 .  
## category_code_LT01_11_count  0.39023    0.11111   3.512 0.000486 ***
## category_code_LT01_13_count  0.02489    0.24388   0.102 0.918750    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6338, Adjusted R-squared:  0.6294 
## F-statistic: 141.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.629356961781572 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0099 -0.7683  0.0471  0.9119  3.6261 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97876    0.08685 114.898  < 2e-16 ***
## category_code_LT01_1_count   0.23971    0.08959   2.676 0.007706 ** 
## category_code_LT01_4_count   0.73606    0.09370   7.855 2.53e-14 ***
## category_code_LT01_5_count   0.93241    0.06183  15.080  < 2e-16 ***
## category_code_LT01_9_count   0.42682    0.22315   1.913 0.056369 .  
## category_code_LT01_11_count  0.39070    0.11102   3.519 0.000473 ***
## category_code_LT01_14_count -0.01901    0.32642  -0.058 0.953592    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6338, Adjusted R-squared:  0.6294 
## F-statistic: 141.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.629402359375596 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0096 -0.7682  0.0597  0.9097  3.6232 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97868    0.08673 115.060  < 2e-16 ***
## category_code_LT01_1_count   0.24308    0.09048   2.687 0.007463 ** 
## category_code_LT01_4_count   0.73622    0.09310   7.908 1.75e-14 ***
## category_code_LT01_5_count   0.93201    0.06149  15.156  < 2e-16 ***
## category_code_LT01_9_count   0.42436    0.22279   1.905 0.057399 .  
## category_code_LT01_11_count  0.39171    0.11109   3.526 0.000461 ***
## category_code_LT01_15_count -0.18998    0.75369  -0.252 0.801095    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6339, Adjusted R-squared:  0.6294 
## F-statistic: 141.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.629967758191604 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0090 -0.7685  0.0505  0.9177  3.6278 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97892    0.08665 115.167  < 2e-16 ***
## category_code_LT01_1_count   0.24109    0.08913   2.705 0.007068 ** 
## category_code_LT01_4_count   0.73303    0.09302   7.881 2.12e-14 ***
## category_code_LT01_5_count   0.93076    0.06146  15.144  < 2e-16 ***
## category_code_LT01_9_count   0.41717    0.22274   1.873 0.061683 .  
## category_code_LT01_11_count  0.38666    0.11102   3.483 0.000541 ***
## category_code_LT01_16_count  1.03951    1.15226   0.902 0.367421    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6344, Adjusted R-squared:   0.63 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 0.620258819456645 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0093 -0.7772  0.0385  0.9208  3.8700 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97194    0.08776 113.631   <2e-16 ***
## category_code_LT01_1_count   0.28848    0.09035   3.193   0.0015 ** 
## category_code_LT01_4_count   0.90245    0.08085  11.162   <2e-16 ***
## category_code_LT01_5_count   0.94137    0.06254  15.052   <2e-16 ***
## category_code_LT01_9_count   0.50070    0.22497   2.226   0.0265 *  
## category_code_LT01_12_count  0.10683    0.20653   0.517   0.6052    
## category_code_LT01_13_count  0.05788    0.24668   0.235   0.8146    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6248, Adjusted R-squared:  0.6203 
## F-statistic: 136.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 0.62022152636596 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0095 -0.7796  0.0326  0.9260  3.8680 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97139    0.08789 113.448  < 2e-16 ***
## category_code_LT01_1_count   0.29214    0.08980   3.253  0.00122 ** 
## category_code_LT01_4_count   0.90500    0.08121  11.144  < 2e-16 ***
## category_code_LT01_5_count   0.94247    0.06279  15.010  < 2e-16 ***
## category_code_LT01_9_count   0.49837    0.22493   2.216  0.02717 *  
## category_code_LT01_12_count  0.10852    0.20693   0.524  0.60023    
## category_code_LT01_14_count -0.02737    0.33107  -0.083  0.93415    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6248, Adjusted R-squared:  0.6202 
## F-statistic: 136.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 0.620224538362312 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0095 -0.7790  0.0377  0.9266  3.8670 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97163    0.08777 113.608  < 2e-16 ***
## category_code_LT01_1_count   0.29319    0.09096   3.223  0.00135 ** 
## category_code_LT01_4_count   0.90471    0.08072  11.208  < 2e-16 ***
## category_code_LT01_5_count   0.94199    0.06249  15.074  < 2e-16 ***
## category_code_LT01_9_count   0.49661    0.22456   2.212  0.02746 *  
## category_code_LT01_12_count  0.10667    0.20666   0.516  0.60599    
## category_code_LT01_15_count -0.07902    0.76296  -0.104  0.91755    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6248, Adjusted R-squared:  0.6202 
## F-statistic: 136.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 0.621034205033613 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0084 -0.7726  0.0398  0.9210  3.8671 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97174    0.08767 113.747  < 2e-16 ***
## category_code_LT01_1_count   0.29297    0.08936   3.278  0.00112 ** 
## category_code_LT01_4_count   0.89933    0.08058  11.161  < 2e-16 ***
## category_code_LT01_5_count   0.94035    0.06244  15.059  < 2e-16 ***
## category_code_LT01_9_count   0.48614    0.22450   2.165  0.03084 *  
## category_code_LT01_12_count  0.10690    0.20630   0.518  0.60457    
## category_code_LT01_16_count  1.19946    1.16514   1.029  0.30377    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6256, Adjusted R-squared:  0.621 
## F-statistic: 136.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 0.620053616654535 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0120 -0.7869  0.0317  0.9179  3.8656 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97197    0.08791 113.431  < 2e-16 ***
## category_code_LT01_1_count   0.29478    0.09009   3.272  0.00114 ** 
## category_code_LT01_4_count   0.90924    0.08076  11.259  < 2e-16 ***
## category_code_LT01_5_count   0.94514    0.06254  15.112  < 2e-16 ***
## category_code_LT01_9_count   0.50341    0.22543   2.233  0.02600 *  
## category_code_LT01_13_count  0.05937    0.24674   0.241  0.80996    
## category_code_LT01_14_count -0.01557    0.33052  -0.047  0.96244    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:  0.6201 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 0.620059770288643 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0118 -0.7860  0.0358  0.9189  3.8646 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97204    0.08779 113.585  < 2e-16 ***
## category_code_LT01_1_count   0.29612    0.09132   3.243  0.00126 ** 
## category_code_LT01_4_count   0.90928    0.08017  11.342  < 2e-16 ***
## category_code_LT01_5_count   0.94485    0.06220  15.191  < 2e-16 ***
## category_code_LT01_9_count   0.50201    0.22511   2.230  0.02619 *  
## category_code_LT01_13_count  0.05723    0.24775   0.231  0.81742    
## category_code_LT01_15_count -0.07724    0.76580  -0.101  0.91970    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:  0.6201 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 0.620883653997471 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0108 -0.7746  0.0352  0.8974  3.8649 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97216    0.08768 113.729  < 2e-16 ***
## category_code_LT01_1_count   0.29546    0.08956   3.299  0.00104 ** 
## category_code_LT01_4_count   0.90360    0.08002  11.292  < 2e-16 ***
## category_code_LT01_5_count   0.94311    0.06215  15.174  < 2e-16 ***
## category_code_LT01_9_count   0.49201    0.22499   2.187  0.02922 *  
## category_code_LT01_13_count  0.06680    0.24655   0.271  0.78654    
## category_code_LT01_16_count  1.21002    1.16585   1.038  0.29983    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.6209 
## F-statistic: 136.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 0.620020455094672 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0121 -0.7908  0.0324  0.9152  3.8624 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97162    0.08793 113.408   <2e-16 ***
## category_code_LT01_1_count   0.29989    0.09060   3.310    0.001 ** 
## category_code_LT01_4_count   0.91167    0.08058  11.314   <2e-16 ***
## category_code_LT01_5_count   0.94579    0.06249  15.136   <2e-16 ***
## category_code_LT01_9_count   0.49917    0.22504   2.218    0.027 *  
## category_code_LT01_14_count -0.01669    0.33051  -0.050    0.960    
## category_code_LT01_15_count -0.09352    0.76268  -0.123    0.902    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:   0.62 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 0.620826971397273 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0111 -0.7803  0.0341  0.9184  3.8627 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.9720048  0.0878201 113.550  < 2e-16 ***
## category_code_LT01_1_count  0.2989320  0.0890615   3.356 0.000851 ***
## category_code_LT01_4_count  0.9056100  0.0805015  11.250  < 2e-16 ***
## category_code_LT01_5_count  0.9438124  0.0624502  15.113  < 2e-16 ***
## category_code_LT01_9_count  0.4880531  0.2250215   2.169 0.030568 *  
## category_code_LT01_14_count 0.0005553  0.3305738   0.002 0.998660    
## category_code_LT01_16_count 1.2011056  1.1669235   1.029 0.303849    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6254, Adjusted R-squared:  0.6208 
## F-statistic: 136.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 0.620834398900729 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0109 -0.7811  0.0375  0.9175  3.8617 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97185    0.08770 113.703  < 2e-16 ***
## category_code_LT01_1_count   0.30052    0.09008   3.336 0.000914 ***
## category_code_LT01_4_count   0.90614    0.07985  11.348  < 2e-16 ***
## category_code_LT01_5_count   0.94383    0.06210  15.198  < 2e-16 ***
## category_code_LT01_9_count   0.48753    0.22460   2.171 0.030436 *  
## category_code_LT01_15_count -0.07475    0.76206  -0.098 0.921903    
## category_code_LT01_16_count  1.19830    1.16577   1.028 0.304505    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6254, Adjusted R-squared:  0.6208 
## F-statistic: 136.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.628155325182491 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9895 -0.7561  0.0489  0.8955  3.4617 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95099    0.09030 110.199  < 2e-16 ***
## category_code_LT01_1_count   0.25221    0.08958   2.815 0.005068 ** 
## category_code_LT01_4_count   0.73967    0.09327   7.931 1.48e-14 ***
## category_code_LT01_5_count   0.94294    0.06167  15.290  < 2e-16 ***
## category_code_LT01_10_count  0.15350    0.11116   1.381 0.167938    
## category_code_LT01_11_count  0.41227    0.11473   3.593 0.000359 ***
## category_code_LT01_12_count -0.09416    0.21146  -0.445 0.656309    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 491 degrees of freedom
## Multiple R-squared:  0.6326, Adjusted R-squared:  0.6282 
## F-statistic: 140.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.628009197146215 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9876 -0.7540  0.0370  0.9187  3.4740 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95083    0.09033 110.160  < 2e-16 ***
## category_code_LT01_1_count   0.24975    0.09008   2.773 0.005773 ** 
## category_code_LT01_4_count   0.74048    0.09338   7.930 1.49e-14 ***
## category_code_LT01_5_count   0.94051    0.06144  15.307  < 2e-16 ***
## category_code_LT01_10_count  0.15197    0.11116   1.367 0.172206    
## category_code_LT01_11_count  0.39963    0.11110   3.597 0.000354 ***
## category_code_LT01_13_count -0.01779    0.24385  -0.073 0.941861    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6325, Adjusted R-squared:  0.628 
## F-statistic: 140.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.628048585505905 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9863 -0.7528  0.0365  0.9016  3.4695 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94850    0.09089 109.462  < 2e-16 ***
## category_code_LT01_1_count   0.25114    0.08978   2.797 0.005357 ** 
## category_code_LT01_4_count   0.74246    0.09376   7.918 1.62e-14 ***
## category_code_LT01_5_count   0.94196    0.06177  15.249  < 2e-16 ***
## category_code_LT01_10_count  0.15763    0.11381   1.385 0.166665    
## category_code_LT01_11_count  0.39916    0.11104   3.595 0.000357 ***
## category_code_LT01_14_count -0.08003    0.33429  -0.239 0.810883    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6325, Adjusted R-squared:  0.628 
## F-statistic: 140.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.628141631840443 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9860 -0.7523  0.0225  0.8995  3.4666 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94939    0.09038 110.090  < 2e-16 ***
## category_code_LT01_1_count   0.25544    0.09060   2.819 0.005006 ** 
## category_code_LT01_4_count   0.74103    0.09329   7.944 1.35e-14 ***
## category_code_LT01_5_count   0.94021    0.06140  15.313  < 2e-16 ***
## category_code_LT01_10_count  0.15573    0.11149   1.397 0.163107    
## category_code_LT01_11_count  0.40068    0.11106   3.608 0.000341 ***
## category_code_LT01_15_count -0.32149    0.75736  -0.424 0.671394    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 491 degrees of freedom
## Multiple R-squared:  0.6326, Adjusted R-squared:  0.6281 
## F-statistic: 140.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.628645225564955 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9874 -0.7536  0.0538  0.8986  3.4811 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95178    0.09025 110.275  < 2e-16 ***
## category_code_LT01_1_count   0.25056    0.08923   2.808 0.005184 ** 
## category_code_LT01_4_count   0.73778    0.09324   7.913 1.68e-14 ***
## category_code_LT01_5_count   0.93889    0.06138  15.297  < 2e-16 ***
## category_code_LT01_10_count  0.14687    0.11114   1.322 0.186941    
## category_code_LT01_11_count  0.39519    0.11104   3.559 0.000408 ***
## category_code_LT01_16_count  1.06206    1.15450   0.920 0.358058    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.372 on 491 degrees of freedom
## Multiple R-squared:  0.6331, Adjusted R-squared:  0.6286 
## F-statistic: 141.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 0.618377770959382 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9836 -0.7744  0.0384  0.9130  3.6965 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.938657   0.091428 108.705  < 2e-16 ***
## category_code_LT01_1_count  0.304426   0.090397   3.368 0.000818 ***
## category_code_LT01_4_count  0.914588   0.080769  11.323  < 2e-16 ***
## category_code_LT01_5_count  0.952304   0.062458  15.247  < 2e-16 ***
## category_code_LT01_10_count 0.178120   0.112454   1.584 0.113853    
## category_code_LT01_12_count 0.097518   0.207301   0.470 0.638264    
## category_code_LT01_13_count 0.008836   0.246875   0.036 0.971462    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.623,  Adjusted R-squared:  0.6184 
## F-statistic: 135.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 0.618442321356576 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9819 -0.7754  0.0328  0.9150  3.6895 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93562    0.09198 108.020  < 2e-16 ***
## category_code_LT01_1_count   0.30744    0.08996   3.418 0.000684 ***
## category_code_LT01_4_count   0.91731    0.08102  11.322  < 2e-16 ***
## category_code_LT01_5_count   0.95424    0.06274  15.209  < 2e-16 ***
## category_code_LT01_10_count  0.18540    0.11505   1.611 0.107718    
## category_code_LT01_12_count  0.10081    0.20757   0.486 0.627422    
## category_code_LT01_14_count -0.09847    0.33905  -0.290 0.771614    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.623,  Adjusted R-squared:  0.6184 
## F-statistic: 135.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 0.618447482547659 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9825 -0.7645  0.0372  0.9106  3.6905 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93744    0.09148 108.624  < 2e-16 ***
## category_code_LT01_1_count   0.30989    0.09106   3.403  0.00072 ***
## category_code_LT01_4_count   0.91598    0.08065  11.357  < 2e-16 ***
## category_code_LT01_5_count   0.95239    0.06242  15.259  < 2e-16 ***
## category_code_LT01_10_count  0.18128    0.11283   1.607  0.10878    
## category_code_LT01_12_count  0.09499    0.20745   0.458  0.64724    
## category_code_LT01_15_count -0.23152    0.76754  -0.302  0.76305    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6231, Adjusted R-squared:  0.6184 
## F-statistic: 135.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 0.619236629535347 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9834 -0.7712  0.0331  0.9189  3.7007 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93973    0.09132 108.849  < 2e-16 ***
## category_code_LT01_1_count   0.30608    0.08944   3.422 0.000673 ***
## category_code_LT01_4_count   0.90985    0.08061  11.287  < 2e-16 ***
## category_code_LT01_5_count   0.95050    0.06238  15.238  < 2e-16 ***
## category_code_LT01_10_count  0.17228    0.11241   1.533 0.126018    
## category_code_LT01_12_count  0.09745    0.20706   0.471 0.638117    
## category_code_LT01_16_count  1.22995    1.16805   1.053 0.292862    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6238, Adjusted R-squared:  0.6192 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 0.61825993665187 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9840 -0.7763  0.0292  0.8984  3.6837 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.935568   0.092020 107.972  < 2e-16 ***
## category_code_LT01_1_count   0.312446   0.090192   3.464 0.000578 ***
## category_code_LT01_4_count   0.922557   0.080489  11.462  < 2e-16 ***
## category_code_LT01_5_count   0.957273   0.062474  15.323  < 2e-16 ***
## category_code_LT01_10_count  0.187521   0.115063   1.630 0.103802    
## category_code_LT01_13_count  0.008453   0.246969   0.034 0.972709    
## category_code_LT01_14_count -0.089409   0.338743  -0.264 0.791934    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6229, Adjusted R-squared:  0.6183 
## F-statistic: 135.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 0.6182846478267 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9842 -0.7688  0.0320  0.9027  3.6839 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93703    0.09152 108.576  < 2e-16 ***
## category_code_LT01_1_count   0.31541    0.09133   3.454 0.000601 ***
## category_code_LT01_4_count   0.92135    0.08003  11.512  < 2e-16 ***
## category_code_LT01_5_count   0.95547    0.06210  15.386  < 2e-16 ***
## category_code_LT01_10_count  0.18416    0.11277   1.633 0.103097    
## category_code_LT01_13_count  0.00269    0.24795   0.011 0.991347    
## category_code_LT01_15_count -0.24537    0.77033  -0.319 0.750223    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6229, Adjusted R-squared:  0.6183 
## F-statistic: 135.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 0.619069303018715 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9853 -0.7603  0.0346  0.9071  3.6950 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93948    0.09135 108.809  < 2e-16 ***
## category_code_LT01_1_count   0.31064    0.08957   3.468 0.000571 ***
## category_code_LT01_4_count   0.91490    0.08000  11.436  < 2e-16 ***
## category_code_LT01_5_count   0.95351    0.06206  15.363  < 2e-16 ***
## category_code_LT01_10_count  0.17480    0.11234   1.556 0.120368    
## category_code_LT01_13_count  0.01866    0.24678   0.076 0.939764    
## category_code_LT01_16_count  1.23326    1.16896   1.055 0.291940    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 0.618342620572481 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9826 -0.7725  0.0245  0.8964  3.6772 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93417    0.09208 107.886  < 2e-16 ***
## category_code_LT01_1_count   0.31826    0.09076   3.507 0.000495 ***
## category_code_LT01_4_count   0.92398    0.08033  11.502  < 2e-16 ***
## category_code_LT01_5_count   0.95733    0.06242  15.336  < 2e-16 ***
## category_code_LT01_10_count  0.19109    0.11544   1.655 0.098508 .  
## category_code_LT01_14_count -0.09258    0.33873  -0.273 0.784728    
## category_code_LT01_15_count -0.25161    0.76724  -0.328 0.743097    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.623,  Adjusted R-squared:  0.6183 
## F-statistic: 135.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 0.619096832078491 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9841 -0.7637  0.0329  0.9112  3.6893 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93725    0.09192 108.113  < 2e-16 ***
## category_code_LT01_1_count   0.31349    0.08918   3.515  0.00048 ***
## category_code_LT01_4_count   0.91730    0.08034  11.418  < 2e-16 ***
## category_code_LT01_5_count   0.95508    0.06240  15.306  < 2e-16 ***
## category_code_LT01_10_count  0.18022    0.11508   1.566  0.11797    
## category_code_LT01_14_count -0.06879    0.33888  -0.203  0.83923    
## category_code_LT01_16_count  1.21622    1.17033   1.039  0.29922    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 0.619130262466754 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9841 -0.7612  0.0355  0.9083  3.6889 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93825    0.09141 108.727  < 2e-16 ***
## category_code_LT01_1_count   0.31626    0.09013   3.509 0.000491 ***
## category_code_LT01_4_count   0.91640    0.07985  11.477  < 2e-16 ***
## category_code_LT01_5_count   0.95363    0.06202  15.377  < 2e-16 ***
## category_code_LT01_10_count  0.17798    0.11271   1.579 0.114943    
## category_code_LT01_15_count -0.22256    0.76652  -0.290 0.771671    
## category_code_LT01_16_count  1.22032    1.16872   1.044 0.296930    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.626711875270196 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0245 -0.7704  0.0252  0.8917  3.5911 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.985297   0.086982 114.797  < 2e-16 ***
## category_code_LT01_1_count   0.249415   0.090505   2.756 0.006072 ** 
## category_code_LT01_4_count   0.754392   0.092961   8.115 3.93e-15 ***
## category_code_LT01_5_count   0.943982   0.061822  15.269  < 2e-16 ***
## category_code_LT01_11_count  0.422196   0.114792   3.678 0.000261 ***
## category_code_LT01_12_count -0.083674   0.211737  -0.395 0.692880    
## category_code_LT01_13_count -0.007256   0.244161  -0.030 0.976306    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6312, Adjusted R-squared:  0.6267 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.62671700138879 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0245 -0.7688  0.0289  0.8943  3.5914 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98572    0.08710 114.644  < 2e-16 ***
## category_code_LT01_1_count   0.24833    0.09012   2.756  0.00607 ** 
## category_code_LT01_4_count   0.75323    0.09358   8.049 6.35e-15 ***
## category_code_LT01_5_count   0.94336    0.06212  15.187  < 2e-16 ***
## category_code_LT01_11_count  0.42217    0.11474   3.679  0.00026 ***
## category_code_LT01_12_count -0.08487    0.21216  -0.400  0.68931    
## category_code_LT01_14_count  0.02861    0.32760   0.087  0.93045    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6312, Adjusted R-squared:  0.6267 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.626791900214761 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0240 -0.7712  0.0210  0.8889  3.5872 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98483    0.08698 114.791  < 2e-16 ***
## category_code_LT01_1_count   0.25416    0.09107   2.791 0.005463 ** 
## category_code_LT01_4_count   0.75519    0.09288   8.131 3.51e-15 ***
## category_code_LT01_5_count   0.94392    0.06178  15.278  < 2e-16 ***
## category_code_LT01_11_count  0.42376    0.11484   3.690 0.000249 ***
## category_code_LT01_12_count -0.08693    0.21195  -0.410 0.681857    
## category_code_LT01_15_count -0.24660    0.75685  -0.326 0.744691    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.627438311839759 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0231 -0.7647  0.0381  0.8865  3.5939 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98505    0.08690 114.909  < 2e-16 ***
## category_code_LT01_1_count   0.25088    0.08966   2.798 0.005342 ** 
## category_code_LT01_4_count   0.75123    0.09281   8.094 4.57e-15 ***
## category_code_LT01_5_count   0.94227    0.06175  15.259  < 2e-16 ***
## category_code_LT01_11_count  0.41702    0.11474   3.635 0.000308 ***
## category_code_LT01_12_count -0.08198    0.21154  -0.388 0.698527    
## category_code_LT01_16_count  1.13074    1.15511   0.979 0.328108    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6319, Adjusted R-squared:  0.6274 
## F-statistic: 140.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.626596023178806 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0225 -0.7646  0.0255  0.9063  3.6016 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.985176   0.087110 114.627  < 2e-16 ***
## category_code_LT01_1_count   0.245942   0.090665   2.713 0.006909 ** 
## category_code_LT01_4_count   0.753967   0.093707   8.046 6.48e-15 ***
## category_code_LT01_5_count   0.941259   0.061929  15.199  < 2e-16 ***
## category_code_LT01_11_count  0.410569   0.111019   3.698 0.000242 ***
## category_code_LT01_13_count -0.007306   0.244229  -0.030 0.976149    
## category_code_LT01_14_count  0.020114   0.327031   0.062 0.950982    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6311, Adjusted R-squared:  0.6266 
## F-statistic:   140 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.626666651197985 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0220 -0.7639  0.0255  0.8984  3.5976 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98440    0.08700 114.768  < 2e-16 ***
## category_code_LT01_1_count   0.25159    0.09169   2.744 0.006291 ** 
## category_code_LT01_4_count   0.75573    0.09302   8.124 3.68e-15 ***
## category_code_LT01_5_count   0.94165    0.06155  15.299  < 2e-16 ***
## category_code_LT01_11_count  0.41191    0.11108   3.708 0.000233 ***
## category_code_LT01_13_count -0.01442    0.24518  -0.059 0.953110    
## category_code_LT01_15_count -0.23606    0.75924  -0.311 0.755992    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6312, Adjusted R-squared:  0.6267 
## F-statistic:   140 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.62732435665266 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0211 -0.7638  0.0335  0.8948  3.6041 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.9846570  0.0869054 114.891  < 2e-16 ***
## category_code_LT01_1_count  0.2479977  0.0901419   2.751 0.006157 ** 
## category_code_LT01_4_count  0.7514965  0.0929386   8.086 4.85e-15 ***
## category_code_LT01_5_count  0.9400009  0.0615192  15.280  < 2e-16 ***
## category_code_LT01_11_count 0.4056572  0.1110220   3.654 0.000286 ***
## category_code_LT01_13_count 0.0004019  0.2440939   0.002 0.998687    
## category_code_LT01_16_count 1.1345150  1.1558829   0.982 0.326823    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6318, Adjusted R-squared:  0.6273 
## F-statistic: 140.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.626666746920205 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0219 -0.7641  0.0262  0.9012  3.5984 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98472    0.08711 114.619  < 2e-16 ***
## category_code_LT01_1_count   0.25028    0.09116   2.746 0.006262 ** 
## category_code_LT01_4_count   0.75474    0.09363   8.061  5.8e-15 ***
## category_code_LT01_5_count   0.94112    0.06188  15.208  < 2e-16 ***
## category_code_LT01_11_count  0.41161    0.11101   3.708 0.000233 ***
## category_code_LT01_14_count  0.01958    0.32697   0.060 0.952266    
## category_code_LT01_15_count -0.23172    0.75616  -0.306 0.759395    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6312, Adjusted R-squared:  0.6267 
## F-statistic:   140 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.627333310696395 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0211 -0.7642  0.0352  0.8980  3.6044 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98515    0.08702 114.745  < 2e-16 ***
## category_code_LT01_1_count   0.24707    0.08979   2.752 0.006150 ** 
## category_code_LT01_4_count   0.75022    0.09357   8.018 7.92e-15 ***
## category_code_LT01_5_count   0.93926    0.06186  15.184  < 2e-16 ***
## category_code_LT01_11_count  0.40554    0.11096   3.655 0.000285 ***
## category_code_LT01_14_count  0.03552    0.32703   0.109 0.913542    
## category_code_LT01_16_count  1.14040    1.15653   0.986 0.324594    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6318, Adjusted R-squared:  0.6273 
## F-statistic: 140.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.627384389638461 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0206 -0.7634  0.0302  0.8908  3.6008 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98423    0.08691 114.882  < 2e-16 ***
## category_code_LT01_1_count   0.25229    0.09065   2.783 0.005589 ** 
## category_code_LT01_4_count   0.75235    0.09286   8.102 4.33e-15 ***
## category_code_LT01_5_count   0.93994    0.06148  15.289  < 2e-16 ***
## category_code_LT01_11_count  0.40675    0.11101   3.664 0.000275 ***
## category_code_LT01_15_count -0.21254    0.75568  -0.281 0.778627    
## category_code_LT01_16_count  1.12585    1.15556   0.974 0.330392    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6319, Adjusted R-squared:  0.6274 
## F-statistic: 140.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616430351627558 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0242 -0.7682  0.0044  0.9342  3.8546 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97861    0.08828 113.038  < 2e-16 ***
## category_code_LT01_1_count   0.30109    0.09101   3.308  0.00101 ** 
## category_code_LT01_4_count   0.93545    0.08065  11.599  < 2e-16 ***
## category_code_LT01_5_count   0.95322    0.06295  15.143  < 2e-16 ***
## category_code_LT01_12_count  0.11415    0.20796   0.549  0.58332    
## category_code_LT01_13_count  0.02180    0.24741   0.088  0.92981    
## category_code_LT01_14_count  0.01893    0.33212   0.057  0.95458    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616445833444088 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0240 -0.7676  0.0027  0.9340  3.8529 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97809    0.08817 113.175  < 2e-16 ***
## category_code_LT01_1_count   0.30426    0.09231   3.296  0.00105 ** 
## category_code_LT01_4_count   0.93698    0.08003  11.709  < 2e-16 ***
## category_code_LT01_5_count   0.95364    0.06261  15.231  < 2e-16 ***
## category_code_LT01_12_count  0.11378    0.20767   0.548  0.58402    
## category_code_LT01_13_count  0.01823    0.24835   0.073  0.94152    
## category_code_LT01_15_count -0.11687    0.76953  -0.152  0.87935    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617426925398362 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0225 -0.7677  0.0107  0.9407  3.8540 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97816    0.08804 113.341  < 2e-16 ***
## category_code_LT01_1_count   0.30251    0.09050   3.343 0.000893 ***
## category_code_LT01_4_count   0.92978    0.07991  11.635  < 2e-16 ***
## category_code_LT01_5_count   0.95144    0.06256  15.209  < 2e-16 ***
## category_code_LT01_12_count  0.11403    0.20727   0.550 0.582452    
## category_code_LT01_13_count  0.03043    0.24718   0.123 0.902071    
## category_code_LT01_16_count  1.32479    1.16992   1.132 0.258029    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616443977106873 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0240 -0.7678  0.0027  0.9351  3.8523 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97828    0.08828 113.024  < 2e-16 ***
## category_code_LT01_1_count   0.30482    0.09164   3.326 0.000946 ***
## category_code_LT01_4_count   0.93685    0.08056  11.629  < 2e-16 ***
## category_code_LT01_5_count   0.95345    0.06291  15.157  < 2e-16 ***
## category_code_LT01_12_count  0.11318    0.20808   0.544 0.586736    
## category_code_LT01_14_count  0.01822    0.33207   0.055 0.956260    
## category_code_LT01_15_count -0.12170    0.76651  -0.159 0.873913    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.61742438126997 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0226 -0.7681  0.0108  0.9415  3.8532 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97857    0.08816 113.190  < 2e-16 ***
## category_code_LT01_1_count   0.30314    0.09002   3.367 0.000819 ***
## category_code_LT01_4_count   0.92929    0.08051  11.543  < 2e-16 ***
## category_code_LT01_5_count   0.95100    0.06286  15.129  < 2e-16 ***
## category_code_LT01_12_count  0.11289    0.20768   0.544 0.586989    
## category_code_LT01_14_count  0.03620    0.33201   0.109 0.913213    
## category_code_LT01_16_count  1.32626    1.17064   1.133 0.257797    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617428535099069 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0224 -0.7674  0.0028  0.9399  3.8518 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97785    0.08805 113.324  < 2e-16 ***
## category_code_LT01_1_count   0.30620    0.09114   3.360 0.000841 ***
## category_code_LT01_4_count   0.93126    0.07983  11.665  < 2e-16 ***
## category_code_LT01_5_count   0.95174    0.06252  15.223  < 2e-16 ***
## category_code_LT01_12_count  0.11333    0.20739   0.546 0.584994    
## category_code_LT01_15_count -0.10049    0.76576  -0.131 0.895646    
## category_code_LT01_16_count  1.31642    1.16969   1.125 0.260951    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616217788811146 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0268 -0.7683 -0.0039  0.9192  3.8482 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97879    0.08831 112.993  < 2e-16 ***
## category_code_LT01_1_count   0.31007    0.09202   3.370 0.000812 ***
## category_code_LT01_4_count   0.94278    0.08001  11.784  < 2e-16 ***
## category_code_LT01_5_count   0.95675    0.06264  15.274  < 2e-16 ***
## category_code_LT01_13_count  0.01973    0.24844   0.079 0.936732    
## category_code_LT01_14_count  0.03010    0.33154   0.091 0.927698    
## category_code_LT01_15_count -0.13143    0.76929  -0.171 0.864413    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.6162 
## F-statistic:   134 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617207748246463 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0254 -0.7687  0.0042  0.9212  3.8496 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97914    0.08818 113.164  < 2e-16 ***
## category_code_LT01_1_count   0.30750    0.09026   3.407 0.000711 ***
## category_code_LT01_4_count   0.93475    0.07997  11.689  < 2e-16 ***
## category_code_LT01_5_count   0.95416    0.06260  15.242  < 2e-16 ***
## category_code_LT01_13_count  0.03264    0.24727   0.132 0.895041    
## category_code_LT01_14_count  0.04847    0.33148   0.146 0.883805    
## category_code_LT01_16_count  1.33531    1.17157   1.140 0.254940    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6172 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617206415864274 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0252 -0.7678  0.0022  0.9203  3.8479 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97823    0.08808 113.290  < 2e-16 ***
## category_code_LT01_1_count   0.31126    0.09142   3.405 0.000716 ***
## category_code_LT01_4_count   0.93735    0.07916  11.842  < 2e-16 ***
## category_code_LT01_5_count   0.95520    0.06221  15.355  < 2e-16 ***
## category_code_LT01_13_count  0.02889    0.24823   0.116 0.907397    
## category_code_LT01_15_count -0.10780    0.76857  -0.140 0.888514    
## category_code_LT01_16_count  1.32261    1.17070   1.130 0.259130    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6172 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617211756463412 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0253 -0.7683  0.0027  0.9338  3.8471 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97878    0.08819 113.147  < 2e-16 ***
## category_code_LT01_1_count   0.31159    0.09079   3.432  0.00065 ***
## category_code_LT01_4_count   0.93638    0.07983  11.730  < 2e-16 ***
## category_code_LT01_5_count   0.95448    0.06255  15.259  < 2e-16 ***
## category_code_LT01_14_count  0.04733    0.33144   0.143  0.88650    
## category_code_LT01_15_count -0.11499    0.76548  -0.150  0.88066    
## category_code_LT01_16_count  1.32586    1.17132   1.132  0.25821    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6172 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 0.601239781506689 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0877 -0.8179  0.0204  0.9578  3.4215 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01287    0.08991 111.371  < 2e-16 ***
## category_code_LT01_1_count   0.42272    0.08765   4.823 1.89e-06 ***
## category_code_LT01_5_count   0.99533    0.06381  15.597  < 2e-16 ***
## category_code_LT01_6_count   0.63652    0.15273   4.168 3.64e-05 ***
## category_code_LT01_7_count   0.57735    0.16070   3.593  0.00036 ***
## category_code_LT01_8_count  -0.18179    0.28217  -0.644  0.51971    
## category_code_LT01_11_count  0.61634    0.10944   5.632 3.01e-08 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.422 on 491 degrees of freedom
## Multiple R-squared:  0.6061, Adjusted R-squared:  0.6012 
## F-statistic: 125.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 0.604194095724545 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0678 -0.8030  0.0383  0.9196  3.4296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00474    0.08961 111.652  < 2e-16 ***
## category_code_LT01_1_count   0.40998    0.08743   4.689 3.56e-06 ***
## category_code_LT01_5_count   0.97839    0.06309  15.509  < 2e-16 ***
## category_code_LT01_6_count   0.60888    0.15244   3.994 7.49e-05 ***
## category_code_LT01_7_count   0.53999    0.16083   3.358 0.000847 ***
## category_code_LT01_9_count   0.46614    0.23069   2.021 0.043859 *  
## category_code_LT01_11_count  0.59764    0.10946   5.460 7.58e-08 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.609,  Adjusted R-squared:  0.6042 
## F-statistic: 127.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 0.601957939889953 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0528 -0.7885  0.0226  0.9788  3.4520 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98240    0.09334 106.950  < 2e-16 ***
## category_code_LT01_1_count   0.42255    0.08753   4.827 1.85e-06 ***
## category_code_LT01_5_count   0.98900    0.06304  15.689  < 2e-16 ***
## category_code_LT01_6_count   0.59995    0.15502   3.870 0.000123 ***
## category_code_LT01_7_count   0.55639    0.16111   3.453 0.000601 ***
## category_code_LT01_10_count  0.13306    0.11663   1.141 0.254461    
## category_code_LT01_11_count  0.61298    0.10938   5.604 3.49e-08 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.421 on 491 degrees of freedom
## Multiple R-squared:  0.6068, Adjusted R-squared:  0.602 
## F-statistic: 126.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 0.601135284894325 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0843 -0.8013  0.0299  0.9621  3.4227 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01170    0.08989 111.376  < 2e-16 ***
## category_code_LT01_1_count   0.42456    0.08790   4.830 1.83e-06 ***
## category_code_LT01_5_count   0.99215    0.06335  15.662  < 2e-16 ***
## category_code_LT01_6_count   0.63822    0.15302   4.171 3.59e-05 ***
## category_code_LT01_7_count   0.56791    0.16091   3.529 0.000456 ***
## category_code_LT01_11_count  0.63545    0.11333   5.607 3.44e-08 ***
## category_code_LT01_12_count -0.11766    0.21989  -0.535 0.592828    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.422 on 491 degrees of freedom
## Multiple R-squared:  0.606,  Adjusted R-squared:  0.6011 
## F-statistic: 125.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 0.600903597048547 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0819 -0.8085  0.0218  0.9662  3.4229 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01146    0.08992 111.341  < 2e-16 ***
## category_code_LT01_1_count   0.42031    0.08860   4.744 2.75e-06 ***
## category_code_LT01_5_count   0.98910    0.06317  15.659  < 2e-16 ***
## category_code_LT01_6_count   0.63218    0.15266   4.141 4.07e-05 ***
## category_code_LT01_7_count   0.57267    0.16162   3.543 0.000433 ***
## category_code_LT01_11_count  0.61939    0.10942   5.660 2.57e-08 ***
## category_code_LT01_13_count  0.00848    0.25372   0.033 0.973350    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.423 on 491 degrees of freedom
## Multiple R-squared:  0.6057, Adjusted R-squared:  0.6009 
## F-statistic: 125.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 0.601764374203578 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0789 -0.8101  0.0382  0.9517  3.4196 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01479    0.08988 111.427  < 2e-16 ***
## category_code_LT01_1_count   0.40702    0.08855   4.597 5.46e-06 ***
## category_code_LT01_5_count   0.97996    0.06368  15.388  < 2e-16 ***
## category_code_LT01_6_count   0.64291    0.15284   4.207 3.08e-05 ***
## category_code_LT01_7_count   0.55948    0.16103   3.474 0.000557 ***
## category_code_LT01_11_count  0.61139    0.10954   5.581 3.95e-08 ***
## category_code_LT01_14_count  0.34735    0.33700   1.031 0.303175    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.421 on 491 degrees of freedom
## Multiple R-squared:  0.6066, Adjusted R-squared:  0.6018 
## F-statistic: 126.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 0.600904953381398 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0819 -0.8112  0.0202  0.9662  3.4230 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01136    0.08993 111.324  < 2e-16 ***
## category_code_LT01_1_count   0.42163    0.08924   4.725 3.01e-06 ***
## category_code_LT01_5_count   0.98918    0.06312  15.671  < 2e-16 ***
## category_code_LT01_6_count   0.63242    0.15277   4.140 4.09e-05 ***
## category_code_LT01_7_count   0.57287    0.16082   3.562 0.000404 ***
## category_code_LT01_11_count  0.61983    0.10956   5.658 2.61e-08 ***
## category_code_LT01_15_count -0.04132    0.78291  -0.053 0.957928    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.423 on 491 degrees of freedom
## Multiple R-squared:  0.6057, Adjusted R-squared:  0.6009 
## F-statistic: 125.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_1_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 0.602633756668945 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0777 -0.8035  0.0270  0.9699  3.4244 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00995    0.08973 111.560  < 2e-16 ***
## category_code_LT01_1_count   0.42088    0.08744   4.813 1.98e-06 ***
## category_code_LT01_5_count   0.98513    0.06305  15.626  < 2e-16 ***
## category_code_LT01_6_count   0.64534    0.15258   4.230 2.79e-05 ***
## category_code_LT01_7_count   0.57314    0.16030   3.576 0.000384 ***
## category_code_LT01_11_count  0.60597    0.10953   5.532 5.14e-08 ***
## category_code_LT01_16_count  1.74675    1.19434   1.463 0.144238    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.42 on 491 degrees of freedom
## Multiple R-squared:  0.6074, Adjusted R-squared:  0.6026 
## F-statistic: 126.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~ new_category_count_col 0.703503546831322 
## 
## Call:
## lm(formula = single.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.7348 -0.6642  0.0180  0.6948  3.9611 
## 
## Coefficients:
##                        Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             9.41698    0.08455  111.38   <2e-16 ***
## new_category_count_col  1.34594    0.03918   34.35   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.226 on 496 degrees of freedom
## Multiple R-squared:  0.7041, Adjusted R-squared:  0.7035 
## F-statistic:  1180 on 1 and 496 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count 0.647020493344259 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9472 -0.7339  0.0096  0.8534  3.5109 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94461    0.08465 117.478  < 2e-16 ***
## category_code_LT01_2_count  0.43371    0.09153   4.738 2.83e-06 ***
## category_code_LT01_3_count  0.21846    0.11174   1.955  0.05114 .  
## category_code_LT01_4_count  0.52210    0.09970   5.237 2.43e-07 ***
## category_code_LT01_5_count  0.89113    0.06023  14.794  < 2e-16 ***
## category_code_LT01_6_count  0.29412    0.14923   1.971  0.04930 *  
## category_code_LT01_7_count  0.39758    0.14982   2.654  0.00822 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.338 on 491 degrees of freedom
## Multiple R-squared:  0.6513, Adjusted R-squared:  0.647 
## F-statistic: 152.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count 0.642202763685869 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9560 -0.7336  0.0862  0.8613  3.4966 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94407    0.08526 116.634  < 2e-16 ***
## category_code_LT01_2_count  0.46521    0.09134   5.093 5.03e-07 ***
## category_code_LT01_3_count  0.22704    0.11249   2.018   0.0441 *  
## category_code_LT01_4_count  0.58351    0.09768   5.974 4.46e-09 ***
## category_code_LT01_5_count  0.90466    0.06120  14.781  < 2e-16 ***
## category_code_LT01_6_count  0.29119    0.15035   1.937   0.0533 .  
## category_code_LT01_8_count -0.15469    0.26691  -0.580   0.5625    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6465, Adjusted R-squared:  0.6422 
## F-statistic: 149.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~ new_category_count_col 0.700443434479773 
## 
## Call:
## lm(formula = single.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.7341 -0.6862  0.0200  0.6444  3.9672 
## 
## Coefficients:
##                        Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             9.41092    0.08523   110.4   <2e-16 ***
## new_category_count_col  1.35368    0.03969    34.1   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.233 on 496 degrees of freedom
## Multiple R-squared:  0.701,  Adjusted R-squared:  0.7004 
## F-statistic:  1163 on 1 and 496 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count 0.643175370663541 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9455 -0.7290  0.0872  0.8758  3.5112 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94055    0.08512 116.779  < 2e-16 ***
## category_code_LT01_2_count  0.45451    0.09165   4.959 9.77e-07 ***
## category_code_LT01_3_count  0.20676    0.11326   1.826   0.0685 .  
## category_code_LT01_4_count  0.57931    0.09759   5.936 5.52e-09 ***
## category_code_LT01_5_count  0.89459    0.06060  14.763  < 2e-16 ***
## category_code_LT01_6_count  0.28131    0.15010   1.874   0.0615 .  
## category_code_LT01_9_count  0.28657    0.22142   1.294   0.1962    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.345 on 491 degrees of freedom
## Multiple R-squared:  0.6475, Adjusted R-squared:  0.6432 
## F-statistic: 150.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count 0.642046751164874 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9433 -0.7360  0.0499  0.8694  3.4684 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93472    0.08821 112.621  < 2e-16 ***
## category_code_LT01_2_count   0.46507    0.09140   5.088 5.16e-07 ***
## category_code_LT01_3_count   0.21938    0.11394   1.925   0.0548 .  
## category_code_LT01_4_count   0.58356    0.09771   5.972 4.49e-09 ***
## category_code_LT01_5_count   0.89980    0.06058  14.853  < 2e-16 ***
## category_code_LT01_6_count   0.28027    0.15176   1.847   0.0654 .  
## category_code_LT01_10_count  0.03907    0.11198   0.349   0.7273    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6464, Adjusted R-squared:  0.642 
## F-statistic: 149.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~ new_category_count_col 0.704587535451595 
## 
## Call:
## lm(formula = single.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.7391 -0.6657 -0.0072  0.6741  3.9331 
## 
## Coefficients:
##                        Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             9.44501    0.08374  112.79   <2e-16 ***
## new_category_count_col  1.31177    0.03808   34.44   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.224 on 496 degrees of freedom
## Multiple R-squared:  0.7052, Adjusted R-squared:  0.7046 
## F-statistic:  1186 on 1 and 496 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count 0.643618023132782 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9574 -0.7393  0.0250  0.8671  3.4977 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94975    0.08518 116.802  < 2e-16 ***
## category_code_LT01_2_count   0.41790    0.09658   4.327 1.83e-05 ***
## category_code_LT01_3_count   0.19353    0.11424   1.694   0.0909 .  
## category_code_LT01_4_count   0.54230    0.10114   5.362 1.27e-07 ***
## category_code_LT01_5_count   0.89845    0.06045  14.864  < 2e-16 ***
## category_code_LT01_6_count   0.26530    0.15066   1.761   0.0789 .  
## category_code_LT01_11_count  0.17926    0.11854   1.512   0.1311    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.345 on 491 degrees of freedom
## Multiple R-squared:  0.6479, Adjusted R-squared:  0.6436 
## F-statistic: 150.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count 0.641986560131774 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9517 -0.7386  0.0423  0.8622  3.5026 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94262    0.08525 116.630  < 2e-16 ***
## category_code_LT01_2_count   0.46819    0.09191   5.094 5.01e-07 ***
## category_code_LT01_3_count   0.22672    0.11262   2.013   0.0446 *  
## category_code_LT01_4_count   0.58401    0.09782   5.970 4.55e-09 ***
## category_code_LT01_5_count   0.90047    0.06077  14.818  < 2e-16 ***
## category_code_LT01_6_count   0.29055    0.15096   1.925   0.0548 .  
## category_code_LT01_12_count -0.04001    0.20222  -0.198   0.8432    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6463, Adjusted R-squared:  0.642 
## F-statistic: 149.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count 0.642029727292823 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9506 -0.7343  0.0465  0.8683  3.5043 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94259    0.08524 116.636  < 2e-16 ***
## category_code_LT01_2_count   0.46478    0.09146   5.082 5.32e-07 ***
## category_code_LT01_3_count   0.22532    0.11250   2.003   0.0457 *  
## category_code_LT01_4_count   0.58022    0.09813   5.913 6.30e-09 ***
## category_code_LT01_5_count   0.89904    0.06060  14.837  < 2e-16 ***
## category_code_LT01_6_count   0.28873    0.15030   1.921   0.0553 .  
## category_code_LT01_13_count  0.07431    0.23695   0.314   0.7539    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6464, Adjusted R-squared:  0.642 
## F-statistic: 149.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count 0.642092290185294 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9504 -0.7336  0.0543  0.8713  3.5055 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94409    0.08530 116.574  < 2e-16 ***
## category_code_LT01_2_count   0.46286    0.09167   5.049 6.26e-07 ***
## category_code_LT01_3_count   0.22796    0.11261   2.024   0.0435 *  
## category_code_LT01_4_count   0.57608    0.09905   5.816 1.09e-08 ***
## category_code_LT01_5_count   0.89654    0.06097  14.705  < 2e-16 ***
## category_code_LT01_6_count   0.29414    0.15100   1.948   0.0520 .  
## category_code_LT01_14_count  0.13776    0.32097   0.429   0.6680    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6464, Adjusted R-squared:  0.6421 
## F-statistic: 149.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count 0.642017495875779 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9504 -0.7425  0.0688  0.8619  3.5045 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94235    0.08525 116.624  < 2e-16 ***
## category_code_LT01_2_count   0.46695    0.09139   5.109 4.64e-07 ***
## category_code_LT01_3_count   0.22949    0.11328   2.026   0.0433 *  
## category_code_LT01_4_count   0.58402    0.09776   5.974 4.45e-09 ***
## category_code_LT01_5_count   0.89901    0.06060  14.834  < 2e-16 ***
## category_code_LT01_6_count   0.28910    0.15035   1.923   0.0551 .  
## category_code_LT01_15_count -0.21009    0.73555  -0.286   0.7753    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6463, Adjusted R-squared:  0.642 
## F-statistic: 149.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_16_count 0.642045657052995 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9510 -0.7362  0.0480  0.8653  3.5039 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94296    0.08525 116.637  < 2e-16 ***
## category_code_LT01_2_count   0.46258    0.09194   5.032 6.84e-07 ***
## category_code_LT01_3_count   0.22145    0.11315   1.957   0.0509 .  
## category_code_LT01_4_count   0.58478    0.09782   5.978 4.35e-09 ***
## category_code_LT01_5_count   0.89898    0.06059  14.836  < 2e-16 ***
## category_code_LT01_6_count   0.29294    0.15102   1.940   0.0530 .  
## category_code_LT01_16_count  0.39899    1.15076   0.347   0.7290    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6464, Adjusted R-squared:  0.642 
## F-statistic: 149.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count 0.644479647915153 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9690 -0.7048  0.0089  0.8403  3.4821 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95440    0.08489 117.259  < 2e-16 ***
## category_code_LT01_2_count  0.47215    0.08968   5.265 2.10e-07 ***
## category_code_LT01_3_count  0.23480    0.11191   2.098  0.03641 *  
## category_code_LT01_4_count  0.55627    0.09857   5.643 2.83e-08 ***
## category_code_LT01_5_count  0.90843    0.06081  14.940  < 2e-16 ***
## category_code_LT01_7_count  0.39568    0.15042   2.631  0.00879 ** 
## category_code_LT01_8_count -0.15682    0.26599  -0.590  0.55575    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6488, Adjusted R-squared:  0.6445 
## F-statistic: 151.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~ new_category_count_col 0.702132763984413 
## 
## Call:
## lm(formula = single.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.7582 -0.6529  0.0121  0.6414  3.9421 
## 
## Coefficients:
##                        Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             9.43597    0.08437  111.84   <2e-16 ***
## new_category_count_col  1.35236    0.03949   34.24   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.229 on 496 degrees of freedom
## Multiple R-squared:  0.7027, Adjusted R-squared:  0.7021 
## F-statistic:  1173 on 1 and 496 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count 0.645151570179928 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9587 -0.7017  0.0242  0.8453  3.4962 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95078    0.08479 117.357  < 2e-16 ***
## category_code_LT01_2_count  0.46318    0.09000   5.147 3.84e-07 ***
## category_code_LT01_3_count  0.21675    0.11274   1.923   0.0551 .  
## category_code_LT01_4_count  0.55426    0.09849   5.628 3.07e-08 ***
## category_code_LT01_5_count  0.89892    0.06020  14.932  < 2e-16 ***
## category_code_LT01_7_count  0.37750    0.15081   2.503   0.0126 *  
## category_code_LT01_9_count  0.25048    0.22157   1.130   0.2588    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.6494, Adjusted R-squared:  0.6452 
## F-statistic: 151.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count 0.644363825000801 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9538 -0.6923  0.0084  0.8468  3.4467 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94284    0.08796 113.043  < 2e-16 ***
## category_code_LT01_2_count   0.47069    0.08983   5.240 2.39e-07 ***
## category_code_LT01_3_count   0.22517    0.11347   1.984   0.0478 *  
## category_code_LT01_4_count   0.55613    0.09859   5.641 2.86e-08 ***
## category_code_LT01_5_count   0.90320    0.06015  15.016  < 2e-16 ***
## category_code_LT01_7_count   0.38819    0.15074   2.575   0.0103 *  
## category_code_LT01_10_count  0.04798    0.11079   0.433   0.6651    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6487, Adjusted R-squared:  0.6444 
## F-statistic: 151.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~ new_category_count_col 0.70489492000893 
## 
## Call:
## lm(formula = single.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.7649 -0.6474  0.0118  0.6555  3.9054 
## 
## Coefficients:
##                        Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             9.47268    0.08308  114.02   <2e-16 ***
## new_category_count_col  1.30903    0.03798   34.47   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.223 on 496 degrees of freedom
## Multiple R-squared:  0.7055, Adjusted R-squared:  0.7049 
## F-statistic:  1188 on 1 and 496 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count 0.645175463936265 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9680 -0.6992  0.0258  0.8606  3.4855 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95763    0.08487 117.326  < 2e-16 ***
## category_code_LT01_2_count   0.43651    0.09505   4.592 5.58e-06 ***
## category_code_LT01_3_count   0.20832    0.11389   1.829   0.0680 .  
## category_code_LT01_4_count   0.52843    0.10135   5.214 2.73e-07 ***
## category_code_LT01_5_count   0.90241    0.06009  15.019  < 2e-16 ***
## category_code_LT01_7_count   0.35361    0.15404   2.296   0.0221 *  
## category_code_LT01_11_count  0.13823    0.12072   1.145   0.2527    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.342 on 491 degrees of freedom
## Multiple R-squared:  0.6495, Adjusted R-squared:  0.6452 
## F-statistic: 151.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count 0.644227974092509 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9637 -0.6968  0.0141  0.8424  3.4895 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.952845   0.084882 117.255  < 2e-16 ***
## category_code_LT01_2_count   0.472941   0.090495   5.226 2.56e-07 ***
## category_code_LT01_3_count   0.233328   0.112080   2.082  0.03788 *  
## category_code_LT01_4_count   0.555890   0.098811   5.626 3.11e-08 ***
## category_code_LT01_5_count   0.903158   0.060400  14.953  < 2e-16 ***
## category_code_LT01_7_count   0.392788   0.150394   2.612  0.00928 ** 
## category_code_LT01_12_count -0.000639   0.200667  -0.003  0.99746    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6485, Adjusted R-squared:  0.6442 
## F-statistic:   151 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count 0.644228400838299 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9638 -0.6969  0.0139  0.8423  3.4895 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.952849   0.084882 117.255  < 2e-16 ***
## category_code_LT01_2_count   0.472969   0.089740   5.270 2.04e-07 ***
## category_code_LT01_3_count   0.233327   0.111927   2.085  0.03762 *  
## category_code_LT01_4_count   0.556021   0.098799   5.628 3.07e-08 ***
## category_code_LT01_5_count   0.903168   0.060172  15.010  < 2e-16 ***
## category_code_LT01_7_count   0.393211   0.151374   2.598  0.00967 ** 
## category_code_LT01_13_count -0.005818   0.237708  -0.024  0.98048    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6485, Adjusted R-squared:  0.6442 
## F-statistic:   151 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count 0.644231339785104 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9637 -0.6964  0.0160  0.8424  3.4897 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95310    0.08496 117.147  < 2e-16 ***
## category_code_LT01_2_count   0.47257    0.08984   5.260 2.15e-07 ***
## category_code_LT01_3_count   0.23373    0.11209   2.085  0.03757 *  
## category_code_LT01_4_count   0.55498    0.09947   5.579 3.99e-08 ***
## category_code_LT01_5_count   0.90272    0.06047  14.928  < 2e-16 ***
## category_code_LT01_7_count   0.39212    0.15071   2.602  0.00955 ** 
## category_code_LT01_14_count  0.02177    0.31910   0.068  0.94563    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6485, Adjusted R-squared:  0.6442 
## F-statistic:   151 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count 0.644239284030414 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9635 -0.6980  0.0126  0.8418  3.4898 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95273    0.08489 117.249  < 2e-16 ***
## category_code_LT01_2_count   0.47337    0.08978   5.273 2.02e-07 ***
## category_code_LT01_3_count   0.23501    0.11275   2.084  0.03764 *  
## category_code_LT01_4_count   0.55646    0.09872   5.637 2.92e-08 ***
## category_code_LT01_5_count   0.90296    0.06018  15.004  < 2e-16 ***
## category_code_LT01_7_count   0.39208    0.15050   2.605  0.00946 ** 
## category_code_LT01_15_count -0.09166    0.73341  -0.125  0.90059    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6485, Adjusted R-squared:  0.6442 
## F-statistic:   151 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_16_count 0.644255797277551 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9639 -0.6955  0.0177  0.8422  3.4894 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95311    0.08489 117.249  < 2e-16 ***
## category_code_LT01_2_count   0.47123    0.09010   5.230 2.51e-07 ***
## category_code_LT01_3_count   0.23107    0.11250   2.054  0.04051 *  
## category_code_LT01_4_count   0.55708    0.09880   5.639 2.90e-08 ***
## category_code_LT01_5_count   0.90295    0.06017  15.007  < 2e-16 ***
## category_code_LT01_7_count   0.39326    0.15041   2.615  0.00921 ** 
## category_code_LT01_16_count  0.22374    1.14160   0.196  0.84470    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6486, Adjusted R-squared:  0.6443 
## F-statistic:   151 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count 0.640840339282294 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9658 -0.7393  0.0735  0.8656  3.4844 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94975    0.08534 116.592  < 2e-16 ***
## category_code_LT01_2_count  0.49038    0.08985   5.458 7.67e-08 ***
## category_code_LT01_3_count  0.22114    0.11343   1.950   0.0518 .  
## category_code_LT01_4_count  0.61141    0.09646   6.338 5.27e-10 ***
## category_code_LT01_5_count  0.91064    0.06117  14.888  < 2e-16 ***
## category_code_LT01_8_count -0.14574    0.26734  -0.545   0.5859    
## category_code_LT01_9_count  0.30411    0.22213   1.369   0.1716    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6452, Adjusted R-squared:  0.6408 
## F-statistic: 148.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count 0.63975363939449 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9573 -0.7272  0.0453  0.8587  3.4147 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93766    0.08852 112.269  < 2e-16 ***
## category_code_LT01_2_count   0.49998    0.08966   5.576 4.06e-08 ***
## category_code_LT01_3_count   0.22963    0.11422   2.011   0.0449 *  
## category_code_LT01_4_count   0.61550    0.09655   6.375 4.23e-10 ***
## category_code_LT01_5_count   0.91581    0.06114  14.978  < 2e-16 ***
## category_code_LT01_8_count  -0.13736    0.26767  -0.513   0.6081    
## category_code_LT01_10_count  0.06926    0.11125   0.623   0.5339    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6441, Adjusted R-squared:  0.6398 
## F-statistic: 148.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count 0.641522226066339 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9770 -0.7474  0.0598  0.8401  3.4722 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95911    0.08534 116.693  < 2e-16 ***
## category_code_LT01_2_count   0.44702    0.09543   4.684 3.64e-06 ***
## category_code_LT01_3_count   0.20450    0.11449   1.786   0.0747 .  
## category_code_LT01_4_count   0.56813    0.10047   5.655 2.65e-08 ***
## category_code_LT01_5_count   0.91318    0.06101  14.967  < 2e-16 ***
## category_code_LT01_8_count  -0.12302    0.26703  -0.461   0.6452    
## category_code_LT01_11_count  0.19845    0.11834   1.677   0.0942 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6458, Adjusted R-squared:  0.6415 
## F-statistic: 149.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count 0.639469316290133 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9717 -0.7393  0.0648  0.8675  3.4765 
## 
## Coefficients:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.9520418  0.0854843 116.419  < 2e-16 ***
## category_code_LT01_2_count   0.5036545  0.0903011   5.578 4.04e-08 ***
## category_code_LT01_3_count   0.2414331  0.1128218   2.140   0.0329 *  
## category_code_LT01_4_count   0.6160858  0.0967885   6.365 4.48e-10 ***
## category_code_LT01_5_count   0.9157245  0.0613761  14.920  < 2e-16 ***
## category_code_LT01_8_count  -0.1340313  0.2678986  -0.500   0.6171    
## category_code_LT01_12_count  0.0008175  0.2021399   0.004   0.9968    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6438, Adjusted R-squared:  0.6395 
## F-statistic: 147.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count 0.639512392812952 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9713 -0.7391  0.0561  0.8678  3.4770 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95198    0.08548 116.426  < 2e-16 ***
## category_code_LT01_2_count   0.50273    0.08958   5.612 3.35e-08 ***
## category_code_LT01_3_count   0.24117    0.11267   2.140   0.0328 *  
## category_code_LT01_4_count   0.61396    0.09699   6.330 5.52e-10 ***
## category_code_LT01_5_count   0.91527    0.06120  14.956  < 2e-16 ***
## category_code_LT01_8_count  -0.13024    0.26815  -0.486   0.6274    
## category_code_LT01_13_count  0.05769    0.23812   0.242   0.8087    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6439, Adjusted R-squared:  0.6395 
## F-statistic: 147.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count 0.639513083136579 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9716 -0.7346  0.0676  0.8675  3.4772 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95298    0.08556 116.321  < 2e-16 ***
## category_code_LT01_2_count   0.50229    0.08968   5.601 3.55e-08 ***
## category_code_LT01_3_count   0.24294    0.11283   2.153   0.0318 *  
## category_code_LT01_4_count   0.61255    0.09768   6.271 7.86e-10 ***
## category_code_LT01_5_count   0.91423    0.06148  14.871  < 2e-16 ***
## category_code_LT01_8_count  -0.13505    0.26774  -0.504   0.6142    
## category_code_LT01_14_count  0.07828    0.32057   0.244   0.8072    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6439, Adjusted R-squared:  0.6395 
## F-statistic: 147.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count 0.639504161070955 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9712 -0.7398  0.0723  0.8679  3.4771 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95184    0.08548 116.417  < 2e-16 ***
## category_code_LT01_2_count   0.50443    0.08955   5.633 2.99e-08 ***
## category_code_LT01_3_count   0.24441    0.11348   2.154   0.0317 *  
## category_code_LT01_4_count   0.61695    0.09666   6.383 4.03e-10 ***
## category_code_LT01_5_count   0.91538    0.06119  14.960  < 2e-16 ***
## category_code_LT01_8_count  -0.13346    0.26771  -0.499   0.6183    
## category_code_LT01_15_count -0.16075    0.73777  -0.218   0.8276    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6439, Adjusted R-squared:  0.6395 
## F-statistic: 147.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_16_count 0.639492473539768 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9719 -0.7396  0.0652  0.8673  3.4763 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95230    0.08549 116.409  < 2e-16 ***
## category_code_LT01_2_count   0.50221    0.08989   5.587 3.83e-08 ***
## category_code_LT01_3_count   0.23944    0.11324   2.115    0.035 *  
## category_code_LT01_4_count   0.61730    0.09681   6.376 4.20e-10 ***
## category_code_LT01_5_count   0.91566    0.06117  14.969  < 2e-16 ***
## category_code_LT01_8_count  -0.13632    0.26803  -0.509    0.611    
## category_code_LT01_16_count  0.20436    1.15045   0.178    0.859    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6438, Adjusted R-squared:  0.6395 
## F-statistic: 147.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count 0.640794167548407 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9500 -0.7268  0.0363  0.8649  3.4428 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93720    0.08836 112.458  < 2e-16 ***
## category_code_LT01_2_count   0.48860    0.08999   5.429 8.91e-08 ***
## category_code_LT01_3_count   0.21143    0.11478   1.842   0.0661 .  
## category_code_LT01_4_count   0.61037    0.09646   6.327 5.62e-10 ***
## category_code_LT01_5_count   0.90589    0.06051  14.972  < 2e-16 ***
## category_code_LT01_9_count   0.28971    0.22309   1.299   0.1947    
## category_code_LT01_10_count  0.05399    0.11160   0.484   0.6288    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6451, Adjusted R-squared:  0.6408 
## F-statistic: 148.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~ new_category_count_col 0.703306291088506 
## 
## Call:
## lm(formula = single.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.7620 -0.6629  0.0302  0.6375  3.9139 
## 
## Coefficients:
##                        Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             9.46419    0.08355  113.28   <2e-16 ***
## new_category_count_col  1.31701    0.03835   34.34   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.227 on 496 degrees of freedom
## Multiple R-squared:  0.7039, Adjusted R-squared:  0.7033 
## F-statistic:  1179 on 1 and 496 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count 0.642615804882538 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9668 -0.7388  0.0366  0.8272  3.4862 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95549    0.08520 116.852  < 2e-16 ***
## category_code_LT01_2_count   0.43558    0.09568   4.552 6.70e-06 ***
## category_code_LT01_3_count   0.18433    0.11516   1.601   0.1101    
## category_code_LT01_4_count   0.56363    0.10033   5.618 3.25e-08 ***
## category_code_LT01_5_count   0.90376    0.06036  14.972  < 2e-16 ***
## category_code_LT01_9_count   0.29017    0.22155   1.310   0.1909    
## category_code_LT01_11_count  0.19554    0.11817   1.655   0.0986 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6469, Adjusted R-squared:  0.6426 
## F-statistic: 149.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count 0.64062301649117 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9611 -0.7365  0.0407  0.8706  3.4911 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.948349   0.085325 116.593  < 2e-16 ***
## category_code_LT01_2_count   0.491150   0.090672   5.417 9.52e-08 ***
## category_code_LT01_3_count   0.220024   0.113602   1.937   0.0533 .  
## category_code_LT01_4_count   0.610755   0.096690   6.317 6.00e-10 ***
## category_code_LT01_5_count   0.905790   0.060760  14.908  < 2e-16 ***
## category_code_LT01_9_count   0.300216   0.222087   1.352   0.1771    
## category_code_LT01_12_count -0.001956   0.201680  -0.010   0.9923    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.645,  Adjusted R-squared:  0.6406 
## F-statistic: 148.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count 0.640718605442336 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9605 -0.7364  0.0377  0.8774  3.4919 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94827    0.08531 116.608  < 2e-16 ***
## category_code_LT01_2_count   0.48933    0.08998   5.438 8.51e-08 ***
## category_code_LT01_3_count   0.21923    0.11345   1.932   0.0539 .  
## category_code_LT01_4_count   0.60744    0.09689   6.269 7.95e-10 ***
## category_code_LT01_5_count   0.90513    0.06054  14.952  < 2e-16 ***
## category_code_LT01_9_count   0.30555    0.22254   1.373   0.1704    
## category_code_LT01_13_count  0.08600    0.23785   0.362   0.7178    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6451, Adjusted R-squared:  0.6407 
## F-statistic: 148.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count 0.640637752805786 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9610 -0.7368  0.0473  0.8750  3.4915 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94890    0.08541 116.481  < 2e-16 ***
## category_code_LT01_2_count   0.49031    0.09001   5.447 8.11e-08 ***
## category_code_LT01_3_count   0.22097    0.11366   1.944   0.0525 .  
## category_code_LT01_4_count   0.60865    0.09755   6.240 9.49e-10 ***
## category_code_LT01_5_count   0.90488    0.06082  14.877  < 2e-16 ***
## category_code_LT01_9_count   0.29801    0.22263   1.339   0.1813    
## category_code_LT01_14_count  0.04563    0.32081   0.142   0.8870    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.645,  Adjusted R-squared:  0.6406 
## F-statistic: 148.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count 0.640643438526409 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9607 -0.7363  0.0525  0.8627  3.4915 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94821    0.08533 116.590  < 2e-16 ***
## category_code_LT01_2_count   0.49166    0.08995   5.466 7.33e-08 ***
## category_code_LT01_3_count   0.22234    0.11432   1.945   0.0524 .  
## category_code_LT01_4_count   0.61137    0.09656   6.331 5.50e-10 ***
## category_code_LT01_5_count   0.90550    0.06054  14.958  < 2e-16 ***
## category_code_LT01_9_count   0.29870    0.22227   1.344   0.1796    
## category_code_LT01_15_count -0.12335    0.73720  -0.167   0.8672    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.645,  Adjusted R-squared:  0.6406 
## F-statistic: 148.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_16_count 0.64063517726849 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9611 -0.7366  0.0443  0.8719  3.4911 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94852    0.08533 116.583  < 2e-16 ***
## category_code_LT01_2_count   0.48997    0.09024   5.429 8.90e-08 ***
## category_code_LT01_3_count   0.21852    0.11399   1.917   0.0558 .  
## category_code_LT01_4_count   0.61156    0.09671   6.323 5.76e-10 ***
## category_code_LT01_5_count   0.90563    0.06053  14.962  < 2e-16 ***
## category_code_LT01_9_count   0.29972    0.22212   1.349   0.1778    
## category_code_LT01_16_count  0.14832    1.14742   0.129   0.8972    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.645,  Adjusted R-squared:  0.6406 
## F-statistic: 148.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count 0.641644033008117 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9586 -0.7333  0.0381  0.8507  3.4172 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94373    0.08836 112.537  < 2e-16 ***
## category_code_LT01_2_count   0.44336    0.09560   4.638 4.52e-06 ***
## category_code_LT01_3_count   0.19133    0.11600   1.649   0.0997 .  
## category_code_LT01_4_count   0.56651    0.10044   5.640 2.87e-08 ***
## category_code_LT01_5_count   0.90892    0.06032  15.069  < 2e-16 ***
## category_code_LT01_10_count  0.06832    0.11094   0.616   0.5383    
## category_code_LT01_11_count  0.19986    0.11829   1.690   0.0917 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.646,  Adjusted R-squared:  0.6416 
## F-statistic: 149.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count 0.639561166036288 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9531 -0.7261  0.0441  0.8646  3.4219 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93654    0.08851 112.259  < 2e-16 ***
## category_code_LT01_2_count   0.50087    0.09045   5.537 5.01e-08 ***
## category_code_LT01_3_count   0.22865    0.11435   1.999   0.0461 *  
## category_code_LT01_4_count   0.61498    0.09677   6.355 4.77e-10 ***
## category_code_LT01_5_count   0.91130    0.06071  15.010  < 2e-16 ***
## category_code_LT01_10_count  0.06820    0.11130   0.613   0.5403    
## category_code_LT01_12_count -0.00639    0.20206  -0.032   0.9748    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6439, Adjusted R-squared:  0.6396 
## F-statistic:   148 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count 0.639608280576586 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9529 -0.7262  0.0344  0.8680  3.4233 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93668    0.08851 112.267  < 2e-16 ***
## category_code_LT01_2_count   0.49950    0.08976   5.565 4.32e-08 ***
## category_code_LT01_3_count   0.22834    0.11422   1.999   0.0461 *  
## category_code_LT01_4_count   0.61254    0.09696   6.318 5.96e-10 ***
## category_code_LT01_5_count   0.91077    0.06049  15.057  < 2e-16 ***
## category_code_LT01_10_count  0.06738    0.11129   0.605   0.5451    
## category_code_LT01_13_count  0.06071    0.23777   0.255   0.7986    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.644,  Adjusted R-squared:  0.6396 
## F-statistic:   148 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count 0.639568102878823 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9535 -0.7270  0.0378  0.8653  3.4248 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93749    0.08899 111.674  < 2e-16 ***
## category_code_LT01_2_count   0.50003    0.08979   5.569 4.23e-08 ***
## category_code_LT01_3_count   0.22956    0.11471   2.001   0.0459 *  
## category_code_LT01_4_count   0.61327    0.09769   6.278 7.56e-10 ***
## category_code_LT01_5_count   0.91047    0.06082  14.969  < 2e-16 ***
## category_code_LT01_10_count  0.06551    0.11413   0.574   0.5663    
## category_code_LT01_14_count  0.03361    0.32877   0.102   0.9186    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6439, Adjusted R-squared:  0.6396 
## F-statistic:   148 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count 0.639609579052015 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9521 -0.7255  0.0309  0.8642  3.4214 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93597    0.08854 112.225  < 2e-16 ***
## category_code_LT01_2_count   0.50127    0.08972   5.587 3.84e-08 ***
## category_code_LT01_3_count   0.23170    0.11490   2.017   0.0443 *  
## category_code_LT01_4_count   0.61577    0.09664   6.372 4.30e-10 ***
## category_code_LT01_5_count   0.91072    0.06049  15.055  < 2e-16 ***
## category_code_LT01_10_count  0.06980    0.11144   0.626   0.5314    
## category_code_LT01_15_count -0.19120    0.73890  -0.259   0.7959    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.644,  Adjusted R-squared:  0.6396 
## F-statistic:   148 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_16_count 0.639574730670092 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9531 -0.7264  0.0446  0.8648  3.4225 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93681    0.08853 112.241  < 2e-16 ***
## category_code_LT01_2_count   0.49934    0.09006   5.545 4.81e-08 ***
## category_code_LT01_3_count   0.22694    0.11476   1.978   0.0485 *  
## category_code_LT01_4_count   0.61571    0.09679   6.361 4.60e-10 ***
## category_code_LT01_5_count   0.91100    0.06048  15.062  < 2e-16 ***
## category_code_LT01_10_count  0.06776    0.11128   0.609   0.5429    
## category_code_LT01_16_count  0.16039    1.14921   0.140   0.8891    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6439, Adjusted R-squared:  0.6396 
## F-statistic:   148 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count 0.641493131134362 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9749 -0.7354  0.0348  0.8428  3.4751 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95849    0.08532 116.718  < 2e-16 ***
## category_code_LT01_2_count   0.44882    0.09553   4.698 3.41e-06 ***
## category_code_LT01_3_count   0.20340    0.11446   1.777   0.0762 .  
## category_code_LT01_4_count   0.56702    0.10045   5.645 2.80e-08 ***
## category_code_LT01_5_count   0.91112    0.06055  15.047  < 2e-16 ***
## category_code_LT01_11_count  0.21143    0.12159   1.739   0.0827 .  
## category_code_LT01_12_count -0.08595    0.20702  -0.415   0.6782    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6458, Adjusted R-squared:  0.6415 
## F-statistic: 149.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count 0.641396118245001 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9726 -0.7421  0.0342  0.8388  3.4784 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95789    0.08532 116.709  < 2e-16 ***
## category_code_LT01_2_count   0.44653    0.09548   4.677 3.77e-06 ***
## category_code_LT01_3_count   0.20302    0.11447   1.774   0.0767 .  
## category_code_LT01_4_count   0.56566    0.10075   5.615 3.30e-08 ***
## category_code_LT01_5_count   0.90870    0.06035  15.057  < 2e-16 ***
## category_code_LT01_11_count  0.19877    0.11844   1.678   0.0939 .  
## category_code_LT01_13_count  0.04718    0.23733   0.199   0.8425    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6457, Adjusted R-squared:  0.6414 
## F-statistic: 149.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~ new_category_count_col 0.701122061715582 
## 
## Call:
## lm(formula = single.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.7828 -0.6306  0.0296  0.6642  3.8887 
## 
## Coefficients:
##                        Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             9.48936    0.08337  113.82   <2e-16 ***
## new_category_count_col  1.31070    0.03837   34.16   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.231 on 496 degrees of freedom
## Multiple R-squared:  0.7017, Adjusted R-squared:  0.7011 
## F-statistic:  1167 on 1 and 496 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count 0.641398609279791 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9727 -0.7416  0.0447  0.8345  3.4787 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95871    0.08540 116.610  < 2e-16 ***
## category_code_LT01_2_count   0.44598    0.09558   4.666 3.97e-06 ***
## category_code_LT01_3_count   0.20437    0.11465   1.783   0.0753 .  
## category_code_LT01_4_count   0.56424    0.10145   5.562 4.39e-08 ***
## category_code_LT01_5_count   0.90766    0.06066  14.962  < 2e-16 ***
## category_code_LT01_11_count  0.19935    0.11835   1.684   0.0927 .  
## category_code_LT01_14_count  0.06624    0.31974   0.207   0.8360    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6457, Adjusted R-squared:  0.6414 
## F-statistic: 149.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count 0.641416331221223 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9724 -0.7423  0.0267  0.8463  3.4787 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95774    0.08532 116.706  < 2e-16 ***
## category_code_LT01_2_count   0.44772    0.09548   4.689 3.56e-06 ***
## category_code_LT01_3_count   0.20643    0.11521   1.792   0.0738 .  
## category_code_LT01_4_count   0.56799    0.10052   5.651 2.71e-08 ***
## category_code_LT01_5_count   0.90855    0.06036  15.053  < 2e-16 ***
## category_code_LT01_11_count  0.20044    0.11835   1.694   0.0910 .  
## category_code_LT01_15_count -0.19077    0.73595  -0.259   0.7956    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6457, Adjusted R-squared:  0.6414 
## F-statistic: 149.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_16_count 0.641395904877713 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9730 -0.7425  0.0287  0.8455  3.4779 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95823    0.08533 116.696  < 2e-16 ***
## category_code_LT01_2_count   0.44521    0.09589   4.643 4.42e-06 ***
## category_code_LT01_3_count   0.20066    0.11510   1.743   0.0819 .  
## category_code_LT01_4_count   0.56831    0.10064   5.647 2.76e-08 ***
## category_code_LT01_5_count   0.90877    0.06034  15.060  < 2e-16 ***
## category_code_LT01_11_count  0.20040    0.11837   1.693   0.0911 .  
## category_code_LT01_16_count  0.22704    1.14643   0.198   0.8431    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6457, Adjusted R-squared:  0.6414 
## F-statistic: 149.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count 0.639339491731101 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9670 -0.7367  0.0628  0.8727  3.4831 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.950703   0.085459 116.438  < 2e-16 ***
## category_code_LT01_2_count   0.503294   0.090387   5.568 4.24e-08 ***
## category_code_LT01_3_count   0.239976   0.112820   2.127   0.0339 *  
## category_code_LT01_4_count   0.613147   0.097184   6.309 6.27e-10 ***
## category_code_LT01_5_count   0.910901   0.060747  14.995  < 2e-16 ***
## category_code_LT01_12_count -0.004126   0.202088  -0.020   0.9837    
## category_code_LT01_13_count  0.064470   0.237843   0.271   0.7865    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count 0.639326997589142 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9672 -0.7254  0.0725  0.8727  3.4834 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.951634   0.085546 116.331  < 2e-16 ***
## category_code_LT01_2_count   0.503155   0.090442   5.563 4.36e-08 ***
## category_code_LT01_3_count   0.241763   0.113004   2.139   0.0329 *  
## category_code_LT01_4_count   0.612115   0.097836   6.257 8.58e-10 ***
## category_code_LT01_5_count   0.909837   0.061026  14.909  < 2e-16 ***
## category_code_LT01_12_count -0.006373   0.202566  -0.031   0.9749    
## category_code_LT01_14_count  0.076381   0.321444   0.238   0.8123    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count 0.639322006839745 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9668 -0.7333  0.0719  0.8729  3.4832 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95053    0.08547 116.427  < 2e-16 ***
## category_code_LT01_2_count   0.50514    0.09038   5.589 3.80e-08 ***
## category_code_LT01_3_count   0.24329    0.11365   2.141   0.0328 *  
## category_code_LT01_4_count   0.61639    0.09689   6.362 4.57e-10 ***
## category_code_LT01_5_count   0.91093    0.06075  14.994  < 2e-16 ***
## category_code_LT01_12_count -0.00424    0.20213  -0.021   0.9833    
## category_code_LT01_15_count -0.16453    0.73825  -0.223   0.8237    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_16_count 0.639302630041008 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9673 -0.7301  0.0690  0.8723  3.4827 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.950932   0.085474 116.420  < 2e-16 ***
## category_code_LT01_2_count   0.503002   0.090725   5.544 4.83e-08 ***
## category_code_LT01_3_count   0.238452   0.113416   2.102    0.036 *  
## category_code_LT01_4_count   0.616477   0.097020   6.354 4.79e-10 ***
## category_code_LT01_5_count   0.911092   0.060746  14.998  < 2e-16 ***
## category_code_LT01_12_count -0.002237   0.202098  -0.011    0.991    
## category_code_LT01_16_count  0.175443   1.149645   0.153    0.879    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count 0.639380398764435 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9667 -0.7366  0.0613  0.8732  3.4840 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95159    0.08554 116.342  < 2e-16 ***
## category_code_LT01_2_count   0.50168    0.08978   5.588 3.81e-08 ***
## category_code_LT01_3_count   0.24129    0.11282   2.139    0.033 *  
## category_code_LT01_4_count   0.60955    0.09808   6.215 1.10e-09 ***
## category_code_LT01_5_count   0.90929    0.06084  14.946  < 2e-16 ***
## category_code_LT01_13_count  0.06455    0.23777   0.271    0.786    
## category_code_LT01_14_count  0.07594    0.32059   0.237    0.813    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6394 
## F-statistic: 147.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count 0.639369962447684 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9665 -0.7364  0.0677  0.8733  3.4838 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95052    0.08546 116.435  < 2e-16 ***
## category_code_LT01_2_count   0.50379    0.08967   5.618 3.23e-08 ***
## category_code_LT01_3_count   0.24265    0.11349   2.138    0.033 *  
## category_code_LT01_4_count   0.61394    0.09709   6.323 5.76e-10 ***
## category_code_LT01_5_count   0.91048    0.06053  15.042  < 2e-16 ***
## category_code_LT01_13_count  0.06110    0.23831   0.256    0.798    
## category_code_LT01_15_count -0.15138    0.73954  -0.205    0.838    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6394 
## F-statistic: 147.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_16_count 0.639358934738484 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9670 -0.7368  0.0638  0.8727  3.4832 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95092    0.08547 116.430  < 2e-16 ***
## category_code_LT01_2_count   0.50165    0.09000   5.574 4.12e-08 ***
## category_code_LT01_3_count   0.23797    0.11325   2.101   0.0361 *  
## category_code_LT01_4_count   0.61405    0.09719   6.318 5.95e-10 ***
## category_code_LT01_5_count   0.91063    0.06052  15.047  < 2e-16 ***
## category_code_LT01_13_count  0.06594    0.23797   0.277   0.7818    
## category_code_LT01_16_count  0.18861    1.15022   0.164   0.8698    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6394 
## F-statistic: 147.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count 0.639363725323981 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9666 -0.7246  0.0752  0.8734  3.4841 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95143    0.08554 116.332  < 2e-16 ***
## category_code_LT01_2_count   0.50352    0.08975   5.610 3.38e-08 ***
## category_code_LT01_3_count   0.24465    0.11364   2.153   0.0318 *  
## category_code_LT01_4_count   0.61278    0.09776   6.268 8.00e-10 ***
## category_code_LT01_5_count   0.90930    0.06085  14.944  < 2e-16 ***
## category_code_LT01_14_count  0.07671    0.32063   0.239   0.8110    
## category_code_LT01_15_count -0.16665    0.73796  -0.226   0.8214    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6394 
## F-statistic: 147.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_16_count 0.639346226461766 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9671 -0.7253  0.0744  0.8728  3.4835 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95187    0.08556 116.321  < 2e-16 ***
## category_code_LT01_2_count   0.50136    0.09011   5.564 4.34e-08 ***
## category_code_LT01_3_count   0.23972    0.11337   2.114    0.035 *  
## category_code_LT01_4_count   0.61292    0.09787   6.263 8.27e-10 ***
## category_code_LT01_5_count   0.90947    0.06084  14.949  < 2e-16 ***
## category_code_LT01_14_count  0.07828    0.32100   0.244    0.807    
## category_code_LT01_16_count  0.18967    1.15072   0.165    0.869    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_15_count+category_code_LT01_16_count 0.639336582166296 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9669 -0.7366  0.0731  0.8729  3.4833 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95072    0.08548 116.417  < 2e-16 ***
## category_code_LT01_2_count   0.50367    0.08998   5.598 3.62e-08 ***
## category_code_LT01_3_count   0.24143    0.11412   2.116   0.0349 *  
## category_code_LT01_4_count   0.61718    0.09689   6.370 4.35e-10 ***
## category_code_LT01_5_count   0.91070    0.06052  15.047  < 2e-16 ***
## category_code_LT01_15_count -0.15904    0.73876  -0.215   0.8296    
## category_code_LT01_16_count  0.16387    1.15063   0.142   0.8868    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 0.627632948101476 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9934 -0.7492  0.0132  0.8562  3.8389 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.96204    0.08693 114.603  < 2e-16 ***
## category_code_LT01_2_count  0.65637    0.08314   7.895 1.91e-14 ***
## category_code_LT01_3_count  0.40735    0.10874   3.746 0.000201 ***
## category_code_LT01_5_count  0.93271    0.06211  15.016  < 2e-16 ***
## category_code_LT01_6_count  0.43249    0.15112   2.862 0.004392 ** 
## category_code_LT01_7_count  0.58175    0.14983   3.883 0.000117 ***
## category_code_LT01_8_count -0.17868    0.27244  -0.656 0.512239    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6321, Adjusted R-squared:  0.6276 
## F-statistic: 140.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 0.628191760936863 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9831 -0.7480  0.0115  0.8837  3.8425 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95849    0.08684 114.674  < 2e-16 ***
## category_code_LT01_2_count  0.64862    0.08348   7.770 4.63e-14 ***
## category_code_LT01_3_count  0.38960    0.10968   3.552 0.000419 ***
## category_code_LT01_5_count  0.92289    0.06153  14.999  < 2e-16 ***
## category_code_LT01_6_count  0.42246    0.15098   2.798 0.005343 ** 
## category_code_LT01_7_count  0.56300    0.15030   3.746 0.000201 ***
## category_code_LT01_9_count  0.24533    0.22693   1.081 0.280196    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 491 degrees of freedom
## Multiple R-squared:  0.6327, Adjusted R-squared:  0.6282 
## F-statistic:   141 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 0.627306768520716 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9878 -0.7487  0.0034  0.8684  3.8405 
## 
## Coefficients:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.9604766  0.0899649 110.715  < 2e-16 ***
## category_code_LT01_2_count   0.6577809  0.0831511   7.911 1.71e-14 ***
## category_code_LT01_3_count   0.4059355  0.1101165   3.686 0.000253 ***
## category_code_LT01_5_count   0.9268536  0.0615086  15.069  < 2e-16 ***
## category_code_LT01_6_count   0.4285014  0.1525369   2.809 0.005165 ** 
## category_code_LT01_7_count   0.5784321  0.1501549   3.852 0.000133 ***
## category_code_LT01_10_count -0.0004876  0.1145235  -0.004 0.996604    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6318, Adjusted R-squared:  0.6273 
## F-statistic: 140.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 0.630370518536854 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9936 -0.7578  0.0659  0.8703  3.8326 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96835    0.08666 115.029  < 2e-16 ***
## category_code_LT01_2_count   0.57854    0.09165   6.313 6.14e-10 ***
## category_code_LT01_3_count   0.34728    0.11215   3.097  0.00207 ** 
## category_code_LT01_5_count   0.92380    0.06126  15.080  < 2e-16 ***
## category_code_LT01_6_count   0.38528    0.15195   2.536  0.01153 *  
## category_code_LT01_7_count   0.49322    0.15505   3.181  0.00156 ** 
## category_code_LT01_11_count  0.24394    0.12092   2.017  0.04420 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6348, Adjusted R-squared:  0.6304 
## F-statistic: 142.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 0.627309017654878 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9875 -0.7487  0.0054  0.8676  3.8406 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96038    0.08693 114.583  < 2e-16 ***
## category_code_LT01_2_count   0.65710    0.08407   7.816 3.34e-14 ***
## category_code_LT01_3_count   0.40548    0.10900   3.720 0.000222 ***
## category_code_LT01_5_count   0.92657    0.06172  15.013  < 2e-16 ***
## category_code_LT01_6_count   0.42754    0.15190   2.815 0.005078 ** 
## category_code_LT01_7_count   0.57832    0.14981   3.860 0.000128 ***
## category_code_LT01_12_count  0.01125    0.20609   0.055 0.956479    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6318, Adjusted R-squared:  0.6273 
## F-statistic: 140.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 0.627397506122662 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9871 -0.7479  0.0077  0.8710  3.8407 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96021    0.08692 114.593  < 2e-16 ***
## category_code_LT01_2_count   0.65570    0.08335   7.867 2.34e-14 ***
## category_code_LT01_3_count   0.40472    0.10881   3.720 0.000222 ***
## category_code_LT01_5_count   0.92628    0.06151  15.059  < 2e-16 ***
## category_code_LT01_6_count   0.42889    0.15105   2.839 0.004708 ** 
## category_code_LT01_7_count   0.57153    0.15109   3.783 0.000174 ***
## category_code_LT01_13_count  0.08396    0.24280   0.346 0.729630    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6319, Adjusted R-squared:  0.6274 
## F-statistic: 140.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 0.628067078113434 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9852 -0.7277  0.0084  0.8612  3.8377 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96328    0.08689 114.669  < 2e-16 ***
## category_code_LT01_2_count   0.64428    0.08415   7.657 1.02e-13 ***
## category_code_LT01_3_count   0.40601    0.10866   3.737 0.000208 ***
## category_code_LT01_5_count   0.91900    0.06193  14.839  < 2e-16 ***
## category_code_LT01_6_count   0.43957    0.15132   2.905 0.003839 ** 
## category_code_LT01_7_count   0.56347    0.15039   3.747 0.000200 ***
## category_code_LT01_14_count  0.32493    0.32432   1.002 0.316904    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6326, Adjusted R-squared:  0.6281 
## F-statistic: 140.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 0.627307375245927 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9878 -0.7488 -0.0035  0.8686  3.8406 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96040    0.08693 114.576  < 2e-16 ***
## category_code_LT01_2_count   0.65763    0.08330   7.895 1.91e-14 ***
## category_code_LT01_3_count   0.40543    0.10982   3.692 0.000248 ***
## category_code_LT01_5_count   0.92690    0.06151  15.069  < 2e-16 ***
## category_code_LT01_6_count   0.42824    0.15118   2.833 0.004806 ** 
## category_code_LT01_7_count   0.57851    0.14987   3.860 0.000128 ***
## category_code_LT01_15_count  0.02145    0.75039   0.029 0.977202    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6318, Adjusted R-squared:  0.6273 
## F-statistic: 140.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 0.627325377270462 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9877 -0.7489  0.0056  0.8687  3.8404 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96055    0.08693 114.578  < 2e-16 ***
## category_code_LT01_2_count   0.65639    0.08361   7.851 2.62e-14 ***
## category_code_LT01_3_count   0.40416    0.10931   3.697 0.000242 ***
## category_code_LT01_5_count   0.92665    0.06151  15.065  < 2e-16 ***
## category_code_LT01_6_count   0.43102    0.15197   2.836 0.004754 ** 
## category_code_LT01_7_count   0.57907    0.14986   3.864 0.000127 ***
## category_code_LT01_16_count  0.18376    1.17319   0.157 0.875595    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6318, Adjusted R-squared:  0.6273 
## F-statistic: 140.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 0.617811744466402 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9992 -0.7548  0.0354  0.8717  3.8419 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95909    0.08808 113.067  < 2e-16 ***
## category_code_LT01_2_count  0.73157    0.08155   8.971  < 2e-16 ***
## category_code_LT01_3_count  0.42866    0.11075   3.871 0.000123 ***
## category_code_LT01_5_count  0.94531    0.06287  15.036  < 2e-16 ***
## category_code_LT01_6_count  0.43774    0.15317   2.858 0.004446 ** 
## category_code_LT01_8_count -0.15487    0.27599  -0.561 0.574954    
## category_code_LT01_9_count  0.32981    0.22916   1.439 0.150722    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6224, Adjusted R-squared:  0.6178 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 0.616253575300738 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9995 -0.7682  0.0061  0.8839  3.8456 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95534    0.09130 109.038  < 2e-16 ***
## category_code_LT01_2_count   0.74647    0.08103   9.212  < 2e-16 ***
## category_code_LT01_3_count   0.44722    0.11127   4.019 6.75e-05 ***
## category_code_LT01_5_count   0.95121    0.06288  15.126  < 2e-16 ***
## category_code_LT01_6_count   0.44028    0.15489   2.843  0.00466 ** 
## category_code_LT01_8_count  -0.14360    0.27644  -0.519  0.60368    
## category_code_LT01_10_count  0.03053    0.11595   0.263  0.79244    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.6163 
## F-statistic:   134 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 0.622904180643884 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0104 -0.7697  0.0433  0.8366  3.8282 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97272    0.08756 113.897  < 2e-16 ***
## category_code_LT01_2_count   0.61555    0.09182   6.704 5.58e-11 ***
## category_code_LT01_3_count   0.35900    0.11328   3.169  0.00162 ** 
## category_code_LT01_5_count   0.94183    0.06240  15.092  < 2e-16 ***
## category_code_LT01_6_count   0.38109    0.15362   2.481  0.01344 *  
## category_code_LT01_8_count  -0.12187    0.27410  -0.445  0.65679    
## category_code_LT01_11_count  0.34735    0.11756   2.955  0.00328 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6275, Adjusted R-squared:  0.6229 
## F-statistic: 137.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 0.616207665856987 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0052 -0.7599  0.0209  0.8738  3.8394 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96152    0.08825 112.878  < 2e-16 ***
## category_code_LT01_2_count   0.74585    0.08201   9.095  < 2e-16 ***
## category_code_LT01_3_count   0.45126    0.11002   4.102  4.8e-05 ***
## category_code_LT01_5_count   0.95041    0.06308  15.066  < 2e-16 ***
## category_code_LT01_6_count   0.44432    0.15421   2.881  0.00413 ** 
## category_code_LT01_8_count  -0.14349    0.27659  -0.519  0.60414    
## category_code_LT01_12_count  0.02152    0.20925   0.103  0.91813    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6162 
## F-statistic:   134 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 0.616711616328064 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0034 -0.7584  0.0188  0.8857  3.8399 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96101    0.08819 112.944  < 2e-16 ***
## category_code_LT01_2_count   0.73980    0.08145   9.083  < 2e-16 ***
## category_code_LT01_3_count   0.44793    0.10982   4.079 5.28e-05 ***
## category_code_LT01_5_count   0.94860    0.06290  15.080  < 2e-16 ***
## category_code_LT01_6_count   0.44639    0.15328   2.912  0.00375 ** 
## category_code_LT01_8_count  -0.13000    0.27668  -0.470  0.63867    
## category_code_LT01_13_count  0.19806    0.24451   0.810  0.41831    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6167 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 0.617665280418564 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0018 -0.7634 -0.0130  0.8868  3.8353 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96561    0.08813 113.075  < 2e-16 ***
## category_code_LT01_2_count   0.72526    0.08240   8.802  < 2e-16 ***
## category_code_LT01_3_count   0.45068    0.10958   4.113 4.58e-05 ***
## category_code_LT01_5_count   0.93965    0.06330  14.845  < 2e-16 ***
## category_code_LT01_6_count   0.46107    0.15349   3.004   0.0028 ** 
## category_code_LT01_8_count  -0.15061    0.27597  -0.546   0.5855    
## category_code_LT01_14_count  0.44905    0.32728   1.372   0.1707    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6223, Adjusted R-squared:  0.6177 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 0.616203962196 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0054 -0.7622  0.0172  0.8752  3.8395 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96144    0.08826 112.870  < 2e-16 ***
## category_code_LT01_2_count   0.74751    0.08112   9.215  < 2e-16 ***
## category_code_LT01_3_count   0.45315    0.11081   4.089 5.05e-05 ***
## category_code_LT01_5_count   0.95080    0.06290  15.116  < 2e-16 ***
## category_code_LT01_6_count   0.44642    0.15350   2.908   0.0038 ** 
## category_code_LT01_8_count  -0.14237    0.27644  -0.515   0.6068    
## category_code_LT01_15_count -0.05816    0.76120  -0.076   0.9391    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6162 
## F-statistic:   134 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 0.616203414378959 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0056 -0.7612  0.0186  0.8762  3.8394 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96160    0.08826 112.868  < 2e-16 ***
## category_code_LT01_2_count   0.74657    0.08143   9.169  < 2e-16 ***
## category_code_LT01_3_count   0.45124    0.11029   4.091 5.01e-05 ***
## category_code_LT01_5_count   0.95088    0.06288  15.121  < 2e-16 ***
## category_code_LT01_6_count   0.44721    0.15436   2.897  0.00393 ** 
## category_code_LT01_8_count  -0.14358    0.27682  -0.519  0.60421    
## category_code_LT01_16_count  0.08541    1.19173   0.072  0.94290    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6162 
## F-statistic:   134 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 0.617578626424732 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9915 -0.7674  0.0360  0.8816  3.8462 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95478    0.09112 109.252  < 2e-16 ***
## category_code_LT01_2_count   0.73233    0.08157   8.978  < 2e-16 ***
## category_code_LT01_3_count   0.42535    0.11201   3.797 0.000165 ***
## category_code_LT01_5_count   0.94038    0.06224  15.108  < 2e-16 ***
## category_code_LT01_6_count   0.43161    0.15455   2.793 0.005431 ** 
## category_code_LT01_9_count   0.32316    0.23012   1.404 0.160864    
## category_code_LT01_10_count  0.01442    0.11624   0.124 0.901331    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6176 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 0.624130556214407 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0002 -0.7587  0.0688  0.8817  3.8318 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96912    0.08740 114.060  < 2e-16 ***
## category_code_LT01_2_count   0.60316    0.09214   6.546 1.49e-10 ***
## category_code_LT01_3_count   0.33708    0.11406   2.955  0.00327 ** 
## category_code_LT01_5_count   0.93228    0.06175  15.097  < 2e-16 ***
## category_code_LT01_6_count   0.37105    0.15330   2.420  0.01586 *  
## category_code_LT01_9_count   0.30493    0.22726   1.342  0.18029    
## category_code_LT01_11_count  0.34374    0.11739   2.928  0.00357 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6241 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 0.617573388825193 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9939 -0.7714  0.0330  0.8793  3.8433 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95768    0.08807 113.062  < 2e-16 ***
## category_code_LT01_2_count   0.73133    0.08256   8.858  < 2e-16 ***
## category_code_LT01_3_count   0.42674    0.11100   3.844 0.000137 ***
## category_code_LT01_5_count   0.93972    0.06246  15.045  < 2e-16 ***
## category_code_LT01_6_count   0.43273    0.15394   2.811 0.005136 ** 
## category_code_LT01_9_count   0.32593    0.22912   1.423 0.155510    
## category_code_LT01_12_count  0.01943    0.20876   0.093 0.925886    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6176 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 0.618239225744238 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9920 -0.7505  0.0359  0.8851  3.8438 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95713    0.08800 113.151  < 2e-16 ***
## category_code_LT01_2_count   0.72339    0.08208   8.814  < 2e-16 ***
## category_code_LT01_3_count   0.42196    0.11082   3.808 0.000158 ***
## category_code_LT01_5_count   0.93779    0.06223  15.070  < 2e-16 ***
## category_code_LT01_6_count   0.43472    0.15296   2.842 0.004668 ** 
## category_code_LT01_9_count   0.33915    0.22937   1.479 0.139878    
## category_code_LT01_13_count  0.22705    0.24412   0.930 0.352789    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6228, Adjusted R-squared:  0.6182 
## F-statistic: 135.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 0.618791747856329 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9911 -0.7511  0.0290  0.8844  3.8394 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96154    0.08799 113.217  < 2e-16 ***
## category_code_LT01_2_count   0.71354    0.08282   8.616  < 2e-16 ***
## category_code_LT01_3_count   0.42773    0.11058   3.868 0.000125 ***
## category_code_LT01_5_count   0.93003    0.06266  14.844  < 2e-16 ***
## category_code_LT01_6_count   0.44849    0.15327   2.926 0.003590 ** 
## category_code_LT01_9_count   0.30349    0.22944   1.323 0.186542    
## category_code_LT01_14_count  0.41166    0.32771   1.256 0.209654    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6234, Adjusted R-squared:  0.6188 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 0.617567023981205 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9942 -0.7658  0.0317  0.8781  3.8433 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95766    0.08808 113.055  < 2e-16 ***
## category_code_LT01_2_count   0.73264    0.08170   8.967  < 2e-16 ***
## category_code_LT01_3_count   0.42777    0.11187   3.824 0.000148 ***
## category_code_LT01_5_count   0.94018    0.06224  15.105  < 2e-16 ***
## category_code_LT01_6_count   0.43437    0.15322   2.835 0.004771 ** 
## category_code_LT01_9_count   0.32561    0.22931   1.420 0.156264    
## category_code_LT01_15_count -0.01684    0.76047  -0.022 0.982345    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6176 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 0.617566856628874 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9943 -0.7650  0.0316  0.8784  3.8433 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95770    0.08808 113.051  < 2e-16 ***
## category_code_LT01_2_count   0.73239    0.08195   8.937  < 2e-16 ***
## category_code_LT01_3_count   0.42725    0.11124   3.841 0.000139 ***
## category_code_LT01_5_count   0.94020    0.06224  15.106  < 2e-16 ***
## category_code_LT01_6_count   0.43452    0.15404   2.821 0.004984 ** 
## category_code_LT01_9_count   0.32574    0.22916   1.421 0.155822    
## category_code_LT01_16_count  0.01972    1.18818   0.017 0.986768    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6176 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 0.622827350878261 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9994 -0.7681  0.0480  0.8480  3.8366 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96438    0.09055 110.038  < 2e-16 ***
## category_code_LT01_2_count   0.61458    0.09189   6.688 6.16e-11 ***
## category_code_LT01_3_count   0.35163    0.11476   3.064   0.0023 ** 
## category_code_LT01_5_count   0.93800    0.06173  15.195  < 2e-16 ***
## category_code_LT01_6_count   0.37116    0.15503   2.394   0.0170 *  
## category_code_LT01_10_count  0.03592    0.11496   0.312   0.7548    
## category_code_LT01_11_count  0.34936    0.11755   2.972   0.0031 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6274, Adjusted R-squared:  0.6228 
## F-statistic: 137.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 0.616047919574537 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9948 -0.7651 -0.0042  0.8955  3.8467 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95421    0.09130 109.029  < 2e-16 ***
## category_code_LT01_2_count   0.74616    0.08204   9.095  < 2e-16 ***
## category_code_LT01_3_count   0.44538    0.11149   3.995 7.47e-05 ***
## category_code_LT01_5_count   0.94596    0.06245  15.148  < 2e-16 ***
## category_code_LT01_6_count   0.43580    0.15562   2.800   0.0053 ** 
## category_code_LT01_10_count  0.02951    0.11598   0.254   0.7992    
## category_code_LT01_12_count  0.01712    0.20919   0.082   0.9348    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.616 
## F-statistic: 133.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 0.616581698331669 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9938 -0.7611 -0.0184  0.9043  3.8466 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95432    0.09124 109.106  < 2e-16 ***
## category_code_LT01_2_count   0.73966    0.08149   9.076  < 2e-16 ***
## category_code_LT01_3_count   0.44232    0.11128   3.975  8.1e-05 ***
## category_code_LT01_5_count   0.94443    0.06222  15.179  < 2e-16 ***
## category_code_LT01_6_count   0.43833    0.15471   2.833   0.0048 ** 
## category_code_LT01_10_count  0.02702    0.11593   0.233   0.8158    
## category_code_LT01_13_count  0.20294    0.24426   0.831   0.4065    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 0.617436654512967 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9984 -0.7650 -0.0212  0.9015  3.8352 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.965784   0.091545 108.862  < 2e-16 ***
## category_code_LT01_2_count   0.726121   0.082417   8.810  < 2e-16 ***
## category_code_LT01_3_count   0.450417   0.111118   4.054 5.87e-05 ***
## category_code_LT01_5_count   0.934520   0.062738  14.896  < 2e-16 ***
## category_code_LT01_6_count   0.459052   0.155396   2.954  0.00329 ** 
## category_code_LT01_10_count -0.007735   0.119085  -0.065  0.94824    
## category_code_LT01_14_count  0.450374   0.336711   1.338  0.18166    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 0.616049663480487 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9948 -0.7657 -0.0078  0.8954  3.8470 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95398    0.09133 108.995  < 2e-16 ***
## category_code_LT01_2_count   0.74761    0.08116   9.212  < 2e-16 ***
## category_code_LT01_3_count   0.44728    0.11216   3.988 7.68e-05 ***
## category_code_LT01_5_count   0.94626    0.06224  15.204  < 2e-16 ***
## category_code_LT01_6_count   0.43755    0.15488   2.825  0.00492 ** 
## category_code_LT01_10_count  0.03024    0.11614   0.260  0.79467    
## category_code_LT01_15_count -0.07203    0.76245  -0.094  0.92477    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.616 
## F-statistic: 133.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 0.616043634087626 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9951 -0.7659 -0.0059  0.8960  3.8467 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95425    0.09132 109.003  < 2e-16 ***
## category_code_LT01_2_count   0.74692    0.08146   9.170  < 2e-16 ***
## category_code_LT01_3_count   0.44560    0.11172   3.989 7.66e-05 ***
## category_code_LT01_5_count   0.94636    0.06223  15.207  < 2e-16 ***
## category_code_LT01_6_count   0.43772    0.15583   2.809  0.00517 ** 
## category_code_LT01_10_count  0.02950    0.11605   0.254  0.79947    
## category_code_LT01_16_count  0.04151    1.19114   0.035  0.97221    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.616 
## F-statistic: 133.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 0.623034198724987 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0091 -0.7878  0.0436  0.8570  3.8288 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97220    0.08751 113.949  < 2e-16 ***
## category_code_LT01_2_count   0.61722    0.09184   6.721 5.02e-11 ***
## category_code_LT01_3_count   0.35748    0.11321   3.158  0.00169 ** 
## category_code_LT01_5_count   0.94062    0.06189  15.198  < 2e-16 ***
## category_code_LT01_6_count   0.38489    0.15385   2.502  0.01269 *  
## category_code_LT01_11_count  0.36534    0.12068   3.027  0.00260 ** 
## category_code_LT01_12_count -0.12897    0.21286  -0.606  0.54487    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6276, Adjusted R-squared:  0.623 
## F-statistic: 137.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 0.623069758235952 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0051 -0.7660  0.0542  0.8500  3.8298 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97115    0.08751 113.945  < 2e-16 ***
## category_code_LT01_2_count   0.61176    0.09199   6.650 7.82e-11 ***
## category_code_LT01_3_count   0.35573    0.11323   3.142  0.00178 ** 
## category_code_LT01_5_count   0.93635    0.06174  15.166  < 2e-16 ***
## category_code_LT01_6_count   0.37953    0.15344   2.473  0.01372 *  
## category_code_LT01_11_count  0.34350    0.11777   2.917  0.00370 ** 
## category_code_LT01_13_count  0.15603    0.24266   0.643  0.52052    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6276, Adjusted R-squared:  0.6231 
## F-statistic: 137.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 0.623795010719611 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0030 -0.7637  0.0716  0.8534  3.8262 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97471    0.08746 114.047  < 2e-16 ***
## category_code_LT01_2_count   0.60081    0.09258   6.489 2.11e-10 ***
## category_code_LT01_3_count   0.35884    0.11310   3.173  0.00160 ** 
## category_code_LT01_5_count   0.92820    0.06218  14.927  < 2e-16 ***
## category_code_LT01_6_count   0.39240    0.15377   2.552  0.01102 *  
## category_code_LT01_11_count  0.33906    0.11767   2.881  0.00413 ** 
## category_code_LT01_14_count  0.37956    0.32538   1.167  0.24396    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6283, Adjusted R-squared:  0.6238 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 0.622772123995862 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0062 -0.7742  0.0514  0.8420  3.8295 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97149    0.08754 113.903  < 2e-16 ***
## category_code_LT01_2_count   0.61616    0.09189   6.706 5.53e-11 ***
## category_code_LT01_3_count   0.35971    0.11412   3.152  0.00172 ** 
## category_code_LT01_5_count   0.93747    0.06175  15.181  < 2e-16 ***
## category_code_LT01_6_count   0.37886    0.15358   2.467  0.01397 *  
## category_code_LT01_11_count  0.34918    0.11758   2.970  0.00313 ** 
## category_code_LT01_15_count -0.12109    0.75490  -0.160  0.87263    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6273, Adjusted R-squared:  0.6228 
## F-statistic: 137.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 0.622765840862669 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0065 -0.7743  0.0491  0.8415  3.8292 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97179    0.08755 113.900  < 2e-16 ***
## category_code_LT01_2_count   0.61438    0.09233   6.655 7.61e-11 ***
## category_code_LT01_3_count   0.35592    0.11383   3.127  0.00187 ** 
## category_code_LT01_5_count   0.93756    0.06174  15.185  < 2e-16 ***
## category_code_LT01_6_count   0.38015    0.15434   2.463  0.01412 *  
## category_code_LT01_11_count  0.34914    0.11759   2.969  0.00313 ** 
## category_code_LT01_16_count  0.15637    1.18037   0.132  0.89466    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6273, Adjusted R-squared:  0.6228 
## F-statistic: 137.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 0.616542241848174 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9989 -0.7548  0.0149  0.8980  3.8412 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95978    0.08818 112.954  < 2e-16 ***
## category_code_LT01_2_count   0.73944    0.08242   8.971  < 2e-16 ***
## category_code_LT01_3_count   0.44609    0.11004   4.054 5.85e-05 ***
## category_code_LT01_5_count   0.94387    0.06244  15.117  < 2e-16 ***
## category_code_LT01_6_count   0.44239    0.15404   2.872  0.00426 ** 
## category_code_LT01_12_count  0.01286    0.20912   0.062  0.95098    
## category_code_LT01_13_count  0.20406    0.24428   0.835  0.40393    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6165 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 0.617434341105583 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9971 -0.7646 -0.0200  0.8974  3.8368 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.964183   0.088121 113.074  < 2e-16 ***
## category_code_LT01_2_count   0.726600   0.083195   8.734  < 2e-16 ***
## category_code_LT01_3_count   0.449473   0.109813   4.093 4.98e-05 ***
## category_code_LT01_5_count   0.934877   0.062836  14.878  < 2e-16 ***
## category_code_LT01_6_count   0.458042   0.154348   2.968  0.00315 ** 
## category_code_LT01_12_count -0.007412   0.209624  -0.035  0.97181    
## category_code_LT01_14_count  0.446273   0.328607   1.358  0.17506    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 0.616002030383174 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0004 -0.7616  0.0228  0.8858  3.8408 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96011    0.08824 112.874  < 2e-16 ***
## category_code_LT01_2_count   0.74716    0.08215   9.095  < 2e-16 ***
## category_code_LT01_3_count   0.45117    0.11108   4.062 5.67e-05 ***
## category_code_LT01_5_count   0.94560    0.06246  15.139  < 2e-16 ***
## category_code_LT01_6_count   0.44177    0.15428   2.863  0.00437 ** 
## category_code_LT01_12_count  0.01737    0.20929   0.083  0.93390    
## category_code_LT01_15_count -0.05932    0.76174  -0.078  0.93796    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.616 
## F-statistic: 133.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 0.615998913192535 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0006 -0.7612  0.0226  0.8875  3.8407 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96023    0.08824 112.872  < 2e-16 ***
## category_code_LT01_2_count   0.74639    0.08245   9.053  < 2e-16 ***
## category_code_LT01_3_count   0.44949    0.11055   4.066 5.57e-05 ***
## category_code_LT01_5_count   0.94565    0.06246  15.141  < 2e-16 ***
## category_code_LT01_6_count   0.44202    0.15505   2.851  0.00454 ** 
## category_code_LT01_12_count  0.01802    0.20921   0.086  0.93141    
## category_code_LT01_16_count  0.05428    1.19052   0.046  0.96365    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.616 
## F-statistic: 133.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 0.61796369388028 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9952 -0.7606  0.0014  0.9059  3.8372 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96376    0.08806 113.147  < 2e-16 ***
## category_code_LT01_2_count   0.71878    0.08284   8.677  < 2e-16 ***
## category_code_LT01_3_count   0.44522    0.10961   4.062 5.66e-05 ***
## category_code_LT01_5_count   0.93285    0.06266  14.886  < 2e-16 ***
## category_code_LT01_6_count   0.45808    0.15329   2.988  0.00294 ** 
## category_code_LT01_13_count  0.20123    0.24374   0.826  0.40944    
## category_code_LT01_14_count  0.44257    0.32710   1.353  0.17667    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616539900995703 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9991 -0.7553  0.0144  0.8968  3.8412 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95976    0.08818 112.948  < 2e-16 ***
## category_code_LT01_2_count   0.74035    0.08162   9.071  < 2e-16 ***
## category_code_LT01_3_count   0.44696    0.11088   4.031 6.44e-05 ***
## category_code_LT01_5_count   0.94416    0.06223  15.172  < 2e-16 ***
## category_code_LT01_6_count   0.44355    0.15330   2.893  0.00398 ** 
## category_code_LT01_13_count  0.20406    0.24467   0.834  0.40467    
## category_code_LT01_15_count -0.02137    0.76235  -0.028  0.97765    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6165 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 0.61654480369826 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9991 -0.7551  0.0139  0.8978  3.8411 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95988    0.08818 112.947  < 2e-16 ***
## category_code_LT01_2_count   0.73948    0.08193   9.026  < 2e-16 ***
## category_code_LT01_3_count   0.44561    0.11035   4.038 6.25e-05 ***
## category_code_LT01_5_count   0.94409    0.06223  15.171  < 2e-16 ***
## category_code_LT01_6_count   0.44482    0.15413   2.886  0.00407 ** 
## category_code_LT01_13_count  0.20546    0.24445   0.840  0.40104    
## category_code_LT01_16_count  0.10009    1.19087   0.084  0.93306    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6165 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 0.617443189413316 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9967 -0.7607 -0.0080  0.8962  3.8369 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96407    0.08812 113.069  < 2e-16 ***
## category_code_LT01_2_count   0.72665    0.08251   8.807  < 2e-16 ***
## category_code_LT01_3_count   0.45091    0.11060   4.077 5.32e-05 ***
## category_code_LT01_5_count   0.93452    0.06269  14.907  < 2e-16 ***
## category_code_LT01_6_count   0.45813    0.15351   2.984  0.00298 ** 
## category_code_LT01_14_count  0.44610    0.32739   1.363  0.17364    
## category_code_LT01_15_count -0.08535    0.76015  -0.112  0.91065    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617447931783118 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9970 -0.7635 -0.0187  0.9018  3.8366 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96435    0.08813 113.066  < 2e-16 ***
## category_code_LT01_2_count   0.72492    0.08294   8.740  < 2e-16 ***
## category_code_LT01_3_count   0.44775    0.11010   4.067 5.56e-05 ***
## category_code_LT01_5_count   0.93447    0.06269  14.906  < 2e-16 ***
## category_code_LT01_6_count   0.45986    0.15441   2.978  0.00304 ** 
## category_code_LT01_14_count  0.44828    0.32805   1.366  0.17242    
## category_code_LT01_16_count  0.16282    1.19086   0.137  0.89130    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 0.615997935337491 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0007 -0.7631  0.0223  0.8876  3.8408 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96016    0.08825 112.864  < 2e-16 ***
## category_code_LT01_2_count   0.74788    0.08157   9.169  < 2e-16 ***
## category_code_LT01_3_count   0.45135    0.11139   4.052 5.91e-05 ***
## category_code_LT01_5_count   0.94599    0.06225  15.198  < 2e-16 ***
## category_code_LT01_6_count   0.44380    0.15432   2.876   0.0042 ** 
## category_code_LT01_15_count -0.05985    0.76220  -0.079   0.9374    
## category_code_LT01_16_count  0.04841    1.19167   0.041   0.9676    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.616 
## F-statistic: 133.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 0.622512626510026 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0161 -0.7601  0.0005  0.8298  3.8274 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97352    0.08741 114.102  < 2e-16 ***
## category_code_LT01_2_count  0.72638    0.07923   9.168  < 2e-16 ***
## category_code_LT01_3_count  0.42931    0.10967   3.914 0.000103 ***
## category_code_LT01_5_count  0.94892    0.06223  15.249  < 2e-16 ***
## category_code_LT01_7_count  0.57454    0.15149   3.793 0.000168 ***
## category_code_LT01_8_count -0.15620    0.27420  -0.570 0.569175    
## category_code_LT01_9_count  0.27232    0.22861   1.191 0.234147    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6271, Adjusted R-squared:  0.6225 
## F-statistic: 137.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 0.621542524486735 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0121 -0.7224 -0.0219  0.8336  3.8346 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96633    0.09067 109.915  < 2e-16 ***
## category_code_LT01_2_count   0.73585    0.07891   9.326  < 2e-16 ***
## category_code_LT01_3_count   0.44033    0.11036   3.990 7.62e-05 ***
## category_code_LT01_5_count   0.95347    0.06220  15.330  < 2e-16 ***
## category_code_LT01_7_count   0.58737    0.15138   3.880 0.000119 ***
## category_code_LT01_8_count  -0.14854    0.27448  -0.541 0.588642    
## category_code_LT01_10_count  0.04526    0.11431   0.396 0.692332    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6261, Adjusted R-squared:  0.6215 
## F-statistic:   137 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 0.625695907807312 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0242 -0.7373  0.0109  0.8068  3.8177 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98324    0.08708 114.647  < 2e-16 ***
## category_code_LT01_2_count   0.63570    0.08941   7.110 4.11e-12 ***
## category_code_LT01_3_count   0.37438    0.11247   3.329 0.000938 ***
## category_code_LT01_5_count   0.94656    0.06192  15.286  < 2e-16 ***
## category_code_LT01_7_count   0.49036    0.15614   3.140 0.001789 ** 
## category_code_LT01_8_count  -0.12717    0.27304  -0.466 0.641592    
## category_code_LT01_11_count  0.28539    0.12053   2.368 0.018278 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6257 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 0.621526528854333 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0198 -0.7331 -0.0047  0.8255  3.8254 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97557    0.08750 114.001  < 2e-16 ***
## category_code_LT01_2_count   0.73211    0.08026   9.122  < 2e-16 ***
## category_code_LT01_3_count   0.44476    0.10903   4.079 5.27e-05 ***
## category_code_LT01_5_count   0.95123    0.06246  15.230  < 2e-16 ***
## category_code_LT01_7_count   0.59106    0.15102   3.914 0.000104 ***
## category_code_LT01_8_count  -0.15038    0.27463  -0.548 0.584237    
## category_code_LT01_12_count  0.07622    0.20669   0.369 0.712450    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6261, Adjusted R-squared:  0.6215 
## F-statistic:   137 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 0.621484452580535 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0208 -0.7579 -0.0001  0.8314  3.8254 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97556    0.08751 113.993  < 2e-16 ***
## category_code_LT01_2_count   0.73618    0.07896   9.323  < 2e-16 ***
## category_code_LT01_3_count   0.44692    0.10876   4.109 4.65e-05 ***
## category_code_LT01_5_count   0.95270    0.06224  15.307  < 2e-16 ***
## category_code_LT01_7_count   0.58579    0.15238   3.844 0.000137 ***
## category_code_LT01_8_count  -0.14178    0.27497  -0.516 0.606350    
## category_code_LT01_13_count  0.06995    0.24517   0.285 0.775524    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6261, Adjusted R-squared:  0.6215 
## F-statistic:   137 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 0.621904400958989 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0201 -0.7355  0.0024  0.8097  3.8226 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97837    0.08752 114.009  < 2e-16 ***
## category_code_LT01_2_count   0.72876    0.07954   9.162  < 2e-16 ***
## category_code_LT01_3_count   0.44887    0.10865   4.131 4.24e-05 ***
## category_code_LT01_5_count   0.94764    0.06258  15.142  < 2e-16 ***
## category_code_LT01_7_count   0.58001    0.15164   3.825 0.000148 ***
## category_code_LT01_8_count  -0.14983    0.27433  -0.546 0.585191    
## category_code_LT01_14_count  0.25822    0.32615   0.792 0.428897    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6265, Adjusted R-squared:  0.6219 
## F-statistic: 137.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 0.621438033022439 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0216 -0.7354 -0.0018  0.8310  3.8251 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97585    0.08752 113.987  < 2e-16 ***
## category_code_LT01_2_count   0.73692    0.07900   9.328  < 2e-16 ***
## category_code_LT01_3_count   0.44558    0.10986   4.056 5.81e-05 ***
## category_code_LT01_5_count   0.95350    0.06222  15.325  < 2e-16 ***
## category_code_LT01_7_count   0.59221    0.15109   3.920 0.000101 ***
## category_code_LT01_8_count  -0.14701    0.27448  -0.536 0.592479    
## category_code_LT01_15_count  0.11000    0.75572   0.146 0.884329    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.626,  Adjusted R-squared:  0.6214 
## F-statistic:   137 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 0.621434206689943 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0212 -0.7367 -0.0023  0.8297  3.8254 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97551    0.08753 113.964  < 2e-16 ***
## category_code_LT01_2_count   0.73856    0.07897   9.352  < 2e-16 ***
## category_code_LT01_3_count   0.44905    0.10910   4.116 4.52e-05 ***
## category_code_LT01_5_count   0.95333    0.06221  15.325  < 2e-16 ***
## category_code_LT01_7_count   0.59095    0.15111   3.911 0.000105 ***
## category_code_LT01_8_count  -0.14488    0.27480  -0.527 0.598290    
## category_code_LT01_16_count -0.14989    1.17674  -0.127 0.898696    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.626,  Adjusted R-squared:  0.6214 
## F-statistic:   137 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 0.62232358557882 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0044 -0.7507 -0.0192  0.8318  3.8356 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96534    0.09055 110.054  < 2e-16 ***
## category_code_LT01_2_count   0.72595    0.07935   9.149  < 2e-16 ***
## category_code_LT01_3_count   0.42295    0.11110   3.807 0.000158 ***
## category_code_LT01_5_count   0.94384    0.06156  15.331  < 2e-16 ***
## category_code_LT01_7_count   0.56911    0.15174   3.750 0.000198 ***
## category_code_LT01_9_count   0.26260    0.22953   1.144 0.253154    
## category_code_LT01_10_count  0.03214    0.11465   0.280 0.779354    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6269, Adjusted R-squared:  0.6223 
## F-statistic: 137.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 0.626545698312474 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.7693  0.0324  0.8317  3.8212 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97974    0.08696 114.761  < 2e-16 ***
## category_code_LT01_2_count   0.62509    0.08976   6.964 1.07e-11 ***
## category_code_LT01_3_count   0.35499    0.11331   3.133  0.00183 ** 
## category_code_LT01_5_count   0.93767    0.06127  15.304  < 2e-16 ***
## category_code_LT01_7_count   0.47122    0.15645   3.012  0.00273 ** 
## category_code_LT01_9_count   0.26260    0.22730   1.155  0.24853    
## category_code_LT01_11_count  0.28556    0.12034   2.373  0.01803 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6311, Adjusted R-squared:  0.6265 
## F-statistic:   140 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 0.622358177434186 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0093 -0.7612 -0.0033  0.8355  3.8292 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97179    0.08739 114.110  < 2e-16 ***
## category_code_LT01_2_count   0.72167    0.08073   8.939  < 2e-16 ***
## category_code_LT01_3_count   0.42491    0.11000   3.863 0.000127 ***
## category_code_LT01_5_count   0.94156    0.06185  15.222  < 2e-16 ***
## category_code_LT01_7_count   0.57118    0.15145   3.771 0.000182 ***
## category_code_LT01_9_count   0.26867    0.22856   1.175 0.240368    
## category_code_LT01_12_count  0.07252    0.20631   0.352 0.725357    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6269, Adjusted R-squared:  0.6224 
## F-statistic: 137.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 0.622391544013218 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0102 -0.7601  0.0005  0.8339  3.8292 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97174    0.08738 114.115  < 2e-16 ***
## category_code_LT01_2_count   0.72443    0.07950   9.112  < 2e-16 ***
## category_code_LT01_3_count   0.42613    0.10975   3.883 0.000117 ***
## category_code_LT01_5_count   0.94290    0.06159  15.310  < 2e-16 ***
## category_code_LT01_7_count   0.56314    0.15290   3.683 0.000256 ***
## category_code_LT01_9_count   0.27563    0.22921   1.202 0.229753    
## category_code_LT01_13_count  0.10016    0.24513   0.409 0.683010    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.627,  Adjusted R-squared:  0.6224 
## F-statistic: 137.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 0.622649061263673 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0099 -0.7575  0.0149  0.8303  3.8266 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97440    0.08742 114.100  < 2e-16 ***
## category_code_LT01_2_count   0.71944    0.07994   8.999  < 2e-16 ***
## category_code_LT01_3_count   0.42952    0.10965   3.917 0.000102 ***
## category_code_LT01_5_count   0.93867    0.06194  15.154  < 2e-16 ***
## category_code_LT01_7_count   0.56201    0.15201   3.697 0.000243 ***
## category_code_LT01_9_count   0.25781    0.22896   1.126 0.260723    
## category_code_LT01_14_count  0.23136    0.32650   0.709 0.478895    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6272, Adjusted R-squared:  0.6226 
## F-statistic: 137.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 0.622289136800552 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0112 -0.7580 -0.0091  0.8328  3.8288 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97211    0.08740 114.102  < 2e-16 ***
## category_code_LT01_2_count   0.72590    0.07952   9.129  < 2e-16 ***
## category_code_LT01_3_count   0.42491    0.11090   3.831 0.000144 ***
## category_code_LT01_5_count   0.94386    0.06157  15.329  < 2e-16 ***
## category_code_LT01_7_count   0.57243    0.15150   3.778 0.000177 ***
## category_code_LT01_9_count   0.27005    0.22873   1.181 0.238320    
## category_code_LT01_15_count  0.13884    0.75535   0.184 0.854235    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6268, Adjusted R-squared:  0.6223 
## F-statistic: 137.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 0.622286717350137 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0107 -0.7581 -0.0155  0.8333  3.8293 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97169    0.08741 114.080  < 2e-16 ***
## category_code_LT01_2_count   0.72807    0.07944   9.165  < 2e-16 ***
## category_code_LT01_3_count   0.42951    0.11005   3.903 0.000108 ***
## category_code_LT01_5_count   0.94376    0.06157  15.329  < 2e-16 ***
## category_code_LT01_7_count   0.57089    0.15154   3.767 0.000185 ***
## category_code_LT01_9_count   0.26922    0.22862   1.178 0.239521    
## category_code_LT01_16_count -0.20554    1.17420  -0.175 0.861113    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6268, Adjusted R-squared:  0.6223 
## F-statistic: 137.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 0.625672763264035 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0098 -0.7598  0.0344  0.8273  3.8292 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97180    0.09019 110.563  < 2e-16 ***
## category_code_LT01_2_count   0.63308    0.08959   7.066 5.48e-12 ***
## category_code_LT01_3_count   0.36414    0.11410   3.191  0.00151 ** 
## category_code_LT01_5_count   0.94227    0.06122  15.393  < 2e-16 ***
## category_code_LT01_7_count   0.48235    0.15643   3.083  0.00216 ** 
## category_code_LT01_10_count  0.04910    0.11368   0.432  0.66598    
## category_code_LT01_11_count  0.28803    0.12050   2.390  0.01721 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6257 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 0.621404781345681 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0060 -0.7437 -0.0164  0.8400  3.8359 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96510    0.09066 109.918  < 2e-16 ***
## category_code_LT01_2_count   0.73126    0.08039   9.097  < 2e-16 ***
## category_code_LT01_3_count   0.43623    0.11064   3.943 9.23e-05 ***
## category_code_LT01_5_count   0.94639    0.06181  15.312  < 2e-16 ***
## category_code_LT01_7_count   0.58415    0.15133   3.860 0.000128 ***
## category_code_LT01_10_count  0.04307    0.11436   0.377 0.706621    
## category_code_LT01_12_count  0.06981    0.20666   0.338 0.735657    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.626,  Adjusted R-squared:  0.6214 
## F-statistic:   137 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 0.621391339206155 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0070 -0.7546 -0.0204  0.8435  3.8359 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96506    0.09066 109.915  < 2e-16 ***
## category_code_LT01_2_count   0.73466    0.07912   9.285  < 2e-16 ***
## category_code_LT01_3_count   0.43806    0.11039   3.968 8.32e-05 ***
## category_code_LT01_5_count   0.94793    0.06153  15.406  < 2e-16 ***
## category_code_LT01_7_count   0.57846    0.15261   3.790 0.000169 ***
## category_code_LT01_10_count  0.04354    0.11433   0.381 0.703479    
## category_code_LT01_13_count  0.07611    0.24478   0.311 0.755991    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.626,  Adjusted R-squared:  0.6214 
## F-statistic:   137 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 0.621712658093617 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0098 -0.7574 -0.0106  0.8264  3.8297 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97126    0.09103 109.534  < 2e-16 ***
## category_code_LT01_2_count   0.72882    0.07959   9.157  < 2e-16 ***
## category_code_LT01_3_count   0.44288    0.11044   4.010 7.02e-05 ***
## category_code_LT01_5_count   0.94302    0.06195  15.223  < 2e-16 ***
## category_code_LT01_7_count   0.57551    0.15179   3.791 0.000168 ***
## category_code_LT01_10_count  0.02598    0.11704   0.222 0.824401    
## category_code_LT01_14_count  0.23950    0.33412   0.717 0.473834    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6263, Adjusted R-squared:  0.6217 
## F-statistic: 137.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 0.621327258901065 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0077 -0.7460 -0.0263  0.8362  3.8356 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96532    0.09070 109.877  < 2e-16 ***
## category_code_LT01_2_count   0.73575    0.07914   9.297  < 2e-16 ***
## category_code_LT01_3_count   0.43724    0.11134   3.927 9.83e-05 ***
## category_code_LT01_5_count   0.94856    0.06152  15.418  < 2e-16 ***
## category_code_LT01_7_count   0.58517    0.15142   3.865 0.000126 ***
## category_code_LT01_10_count  0.04333    0.11454   0.378 0.705335    
## category_code_LT01_15_count  0.08820    0.75721   0.116 0.907317    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6259, Adjusted R-squared:  0.6213 
## F-statistic: 136.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 0.621337149279853 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0070 -0.7454 -0.0284  0.8378  3.8362 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96471    0.09069 109.872  < 2e-16 ***
## category_code_LT01_2_count   0.73734    0.07912   9.319  < 2e-16 ***
## category_code_LT01_3_count   0.44039    0.11072   3.978 8.01e-05 ***
## category_code_LT01_5_count   0.94851    0.06152  15.419  < 2e-16 ***
## category_code_LT01_7_count   0.58379    0.15142   3.855 0.000131 ***
## category_code_LT01_10_count  0.04459    0.11435   0.390 0.696780    
## category_code_LT01_16_count -0.19102    1.17580  -0.162 0.871010    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6259, Adjusted R-squared:  0.6213 
## F-statistic: 136.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 0.625575234375501 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0212 -0.7695  0.0182  0.8142  3.8186 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98234    0.08706 114.657  < 2e-16 ***
## category_code_LT01_2_count   0.63674    0.08956   7.110 4.12e-12 ***
## category_code_LT01_3_count   0.37284    0.11243   3.316  0.00098 ***
## category_code_LT01_5_count   0.94355    0.06147  15.349  < 2e-16 ***
## category_code_LT01_7_count   0.48509    0.15630   3.104  0.00202 ** 
## category_code_LT01_11_count  0.29447    0.12430   2.369  0.01822 *  
## category_code_LT01_12_count -0.05131    0.21192  -0.242  0.80879    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6256 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 0.625575004148832 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0196 -0.7655  0.0241  0.8176  3.8191 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98188    0.08705 114.664  < 2e-16 ***
## category_code_LT01_2_count   0.63450    0.08953   7.087 4.78e-12 ***
## category_code_LT01_3_count   0.37208    0.11244   3.309  0.00100 ** 
## category_code_LT01_5_count   0.94184    0.06124  15.379  < 2e-16 ***
## category_code_LT01_7_count   0.48284    0.15712   3.073  0.00224 ** 
## category_code_LT01_11_count  0.28613    0.12056   2.373  0.01801 *  
## category_code_LT01_13_count  0.05881    0.24351   0.241  0.80927    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6256 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 0.625911394195205 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0187 -0.7629  0.0238  0.8184  3.8167 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98424    0.08707 114.670  < 2e-16 ***
## category_code_LT01_2_count   0.62854    0.08993   6.989 9.05e-12 ***
## category_code_LT01_3_count   0.37420    0.11239   3.329 0.000936 ***
## category_code_LT01_5_count   0.93711    0.06162  15.209  < 2e-16 ***
## category_code_LT01_7_count   0.47798    0.15652   3.054 0.002382 ** 
## category_code_LT01_11_count  0.28417    0.12051   2.358 0.018758 *  
## category_code_LT01_14_count  0.22948    0.32457   0.707 0.479884    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6304, Adjusted R-squared:  0.6259 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 0.625531941084013 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0200 -0.7698  0.0176  0.8168  3.8189 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98203    0.08706 114.658  < 2e-16 ***
## category_code_LT01_2_count   0.63536    0.08953   7.096  4.5e-12 ***
## category_code_LT01_3_count   0.37198    0.11336   3.281  0.00111 ** 
## category_code_LT01_5_count   0.94226    0.06124  15.387  < 2e-16 ***
## category_code_LT01_7_count   0.48755    0.15615   3.122  0.00190 ** 
## category_code_LT01_11_count  0.28686    0.12060   2.379  0.01776 *  
## category_code_LT01_15_count  0.03234    0.75222   0.043  0.96573    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6255 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 0.625533725657148 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0199 -0.7694  0.0212  0.8169  3.8191 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98189    0.08707 114.637  < 2e-16 ***
## category_code_LT01_2_count   0.63603    0.08972   7.089 4.74e-12 ***
## category_code_LT01_3_count   0.37328    0.11291   3.306  0.00102 ** 
## category_code_LT01_5_count   0.94225    0.06123  15.389  < 2e-16 ***
## category_code_LT01_7_count   0.48710    0.15607   3.121  0.00191 ** 
## category_code_LT01_11_count  0.28678    0.12058   2.378  0.01777 *  
## category_code_LT01_16_count -0.07570    1.16977  -0.065  0.94843    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6255 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 0.621368693847484 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0144 -0.7635 -0.0043  0.8315  3.8270 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97394    0.08748 114.013  < 2e-16 ***
## category_code_LT01_2_count   0.73131    0.08044   9.091  < 2e-16 ***
## category_code_LT01_3_count   0.44244    0.10906   4.057 5.79e-05 ***
## category_code_LT01_5_count   0.94580    0.06182  15.298  < 2e-16 ***
## category_code_LT01_7_count   0.58205    0.15226   3.823 0.000149 ***
## category_code_LT01_12_count  0.07029    0.20666   0.340 0.733921    
## category_code_LT01_13_count  0.07547    0.24483   0.308 0.758009    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6259, Adjusted R-squared:  0.6214 
## F-statistic: 136.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 0.621738089386113 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0138 -0.7520  0.0068  0.8266  3.8244 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97660    0.08750 114.017  < 2e-16 ***
## category_code_LT01_2_count   0.72521    0.08087   8.967  < 2e-16 ***
## category_code_LT01_3_count   0.44479    0.10899   4.081 5.23e-05 ***
## category_code_LT01_5_count   0.94104    0.06216  15.140  < 2e-16 ***
## category_code_LT01_7_count   0.57710    0.15159   3.807 0.000158 ***
## category_code_LT01_12_count  0.05943    0.20715   0.287 0.774324    
## category_code_LT01_14_count  0.24805    0.32723   0.758 0.448795    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6263, Adjusted R-squared:  0.6217 
## F-statistic: 137.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 0.621312572487 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0151 -0.7536 -0.0099  0.8255  3.8268 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97418    0.08749 114.004  < 2e-16 ***
## category_code_LT01_2_count   0.73198    0.08054   9.089  < 2e-16 ***
## category_code_LT01_3_count   0.44095    0.11021   4.001 7.28e-05 ***
## category_code_LT01_5_count   0.94639    0.06182  15.309  < 2e-16 ***
## category_code_LT01_7_count   0.58880    0.15102   3.899  0.00011 ***
## category_code_LT01_12_count  0.07281    0.20667   0.352  0.72478    
## category_code_LT01_15_count  0.11278    0.75607   0.149  0.88149    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6259, Adjusted R-squared:  0.6213 
## F-statistic: 136.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 0.621311490217618 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0147 -0.7579 -0.0120  0.8302  3.8271 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97384    0.08750 113.985  < 2e-16 ***
## category_code_LT01_2_count   0.73385    0.08050   9.116  < 2e-16 ***
## category_code_LT01_3_count   0.44473    0.10945   4.063 5.63e-05 ***
## category_code_LT01_5_count   0.94634    0.06182  15.309  < 2e-16 ***
## category_code_LT01_7_count   0.58751    0.15104   3.890 0.000114 ***
## category_code_LT01_12_count  0.07122    0.20667   0.345 0.730550    
## category_code_LT01_16_count -0.16978    1.17591  -0.144 0.885259    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6259, Adjusted R-squared:  0.6213 
## F-statistic: 136.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 0.621753358676536 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.7583  0.0055  0.8237  3.8243 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97670    0.08750 114.024  < 2e-16 ***
## category_code_LT01_2_count   0.72753    0.07976   9.121  < 2e-16 ***
## category_code_LT01_3_count   0.44627    0.10868   4.106 4.71e-05 ***
## category_code_LT01_5_count   0.94209    0.06194  15.211  < 2e-16 ***
## category_code_LT01_7_count   0.57085    0.15290   3.734 0.000211 ***
## category_code_LT01_13_count  0.07817    0.24462   0.320 0.749429    
## category_code_LT01_14_count  0.25582    0.32618   0.784 0.433244    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6263, Adjusted R-squared:  0.6218 
## F-statistic: 137.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 0.621299032912271 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0162 -0.7555 -0.0128  0.8285  3.8267 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97424    0.08749 114.004  < 2e-16 ***
## category_code_LT01_2_count   0.73547    0.07925   9.280  < 2e-16 ***
## category_code_LT01_3_count   0.44277    0.10992   4.028 6.52e-05 ***
## category_code_LT01_5_count   0.94800    0.06155  15.403  < 2e-16 ***
## category_code_LT01_7_count   0.58289    0.15230   3.827 0.000146 ***
## category_code_LT01_13_count  0.08004    0.24521   0.326 0.744256    
## category_code_LT01_15_count  0.12052    0.75718   0.159 0.873604    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6259, Adjusted R-squared:  0.6213 
## F-statistic: 136.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 0.621294600284244 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0158 -0.7635 -0.0160  0.8380  3.8271 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97390    0.08750 113.984  < 2e-16 ***
## category_code_LT01_2_count   0.73735    0.07921   9.309  < 2e-16 ***
## category_code_LT01_3_count   0.44666    0.10915   4.092    5e-05 ***
## category_code_LT01_5_count   0.94792    0.06154  15.403  < 2e-16 ***
## category_code_LT01_7_count   0.58188    0.15233   3.820 0.000151 ***
## category_code_LT01_13_count  0.07624    0.24499   0.311 0.755789    
## category_code_LT01_16_count -0.16467    1.17661  -0.140 0.888756    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6259, Adjusted R-squared:  0.6213 
## F-statistic: 136.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 0.621686117025381 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0153 -0.7463 -0.0003  0.8216  3.8240 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97692    0.08751 114.015  < 2e-16 ***
## category_code_LT01_2_count   0.72866    0.07978   9.134  < 2e-16 ***
## category_code_LT01_3_count   0.44535    0.10980   4.056 5.81e-05 ***
## category_code_LT01_5_count   0.94277    0.06193  15.222  < 2e-16 ***
## category_code_LT01_7_count   0.57778    0.15167   3.810 0.000157 ***
## category_code_LT01_14_count  0.25464    0.32629   0.780 0.435528    
## category_code_LT01_15_count  0.09204    0.75564   0.122 0.903102    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6263, Adjusted R-squared:  0.6217 
## F-statistic: 137.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 0.621683897833116 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0150 -0.7477 -0.0026  0.8215  3.8243 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97664    0.08752 113.990  < 2e-16 ***
## category_code_LT01_2_count   0.73008    0.07981   9.148  < 2e-16 ***
## category_code_LT01_3_count   0.44830    0.10904   4.111 4.61e-05 ***
## category_code_LT01_5_count   0.94271    0.06193  15.223  < 2e-16 ***
## category_code_LT01_7_count   0.57681    0.15165   3.804 0.000161 ***
## category_code_LT01_14_count  0.25354    0.32673   0.776 0.438117    
## category_code_LT01_16_count -0.12868    1.17682  -0.109 0.912972    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6263, Adjusted R-squared:  0.6217 
## F-statistic: 137.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 0.621233382905003 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0165 -0.7575 -0.0179  0.8284  3.8268 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97413    0.08751 113.973  < 2e-16 ***
## category_code_LT01_2_count   0.73837    0.07925   9.317  < 2e-16 ***
## category_code_LT01_3_count   0.44561    0.11032   4.039 6.22e-05 ***
## category_code_LT01_5_count   0.94858    0.06153  15.416  < 2e-16 ***
## category_code_LT01_7_count   0.58861    0.15111   3.895 0.000112 ***
## category_code_LT01_15_count  0.10003    0.75688   0.132 0.894913    
## category_code_LT01_16_count -0.17229    1.17719  -0.146 0.883701    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6258, Adjusted R-squared:  0.6212 
## F-statistic: 136.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 0.611664462399198 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0151 -0.7500  0.0324  0.8660  3.8405 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96041    0.09183 108.461  < 2e-16 ***
## category_code_LT01_2_count   0.81145    0.07705  10.532  < 2e-16 ***
## category_code_LT01_3_count   0.45910    0.11229   4.089 5.07e-05 ***
## category_code_LT01_5_count   0.96628    0.06295  15.350  < 2e-16 ***
## category_code_LT01_8_count  -0.12519    0.27801  -0.450    0.653    
## category_code_LT01_9_count   0.34263    0.23193   1.477    0.140    
## category_code_LT01_10_count  0.05982    0.11605   0.515    0.606    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6164, Adjusted R-squared:  0.6117 
## F-statistic: 131.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 0.61975686740347 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0286 -0.7714  0.0161  0.8120  4.1172 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98307    0.08778 113.723  < 2e-16 ***
## category_code_LT01_2_count   0.65700    0.08995   7.304 1.13e-12 ***
## category_code_LT01_3_count   0.36139    0.11437   3.160  0.00168 ** 
## category_code_LT01_5_count   0.95308    0.06242  15.270  < 2e-16 ***
## category_code_LT01_8_count  -0.10425    0.27511  -0.379  0.70490    
## category_code_LT01_9_count   0.32641    0.22857   1.428  0.15392    
## category_code_LT01_11_count  0.38282    0.11692   3.274  0.00113 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6243, Adjusted R-squared:  0.6198 
## F-statistic:   136 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 0.611583747090833 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0254 -0.7621  0.0313  0.8723  3.8284 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97257    0.08867 112.473  < 2e-16 ***
## category_code_LT01_2_count   0.80789    0.07849  10.293  < 2e-16 ***
## category_code_LT01_3_count   0.46514    0.11109   4.187 3.35e-05 ***
## category_code_LT01_5_count   0.96370    0.06322  15.242  < 2e-16 ***
## category_code_LT01_8_count  -0.12697    0.27819  -0.456    0.648    
## category_code_LT01_9_count   0.35447    0.23086   1.535    0.125    
## category_code_LT01_12_count  0.08469    0.20937   0.404    0.686    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6163, Adjusted R-squared:  0.6116 
## F-statistic: 131.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 0.612080761833396 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0247 -0.7617  0.0280  0.8977  3.8288 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97211    0.08861 112.537  < 2e-16 ***
## category_code_LT01_2_count   0.80563    0.07742  10.406  < 2e-16 ***
## category_code_LT01_3_count   0.46330    0.11084   4.180 3.45e-05 ***
## category_code_LT01_5_count   0.96327    0.06299  15.292  < 2e-16 ***
## category_code_LT01_8_count  -0.10928    0.27823  -0.393    0.695    
## category_code_LT01_9_count   0.36679    0.23114   1.587    0.113    
## category_code_LT01_13_count  0.21944    0.24644   0.890    0.374    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6168, Adjusted R-squared:  0.6121 
## F-statistic: 131.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 0.612309677048717 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0255 -0.7660  0.0418  0.8609  3.8246 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97639    0.08865 112.535  < 2e-16 ***
## category_code_LT01_2_count   0.80075    0.07788  10.282  < 2e-16 ***
## category_code_LT01_3_count   0.47008    0.11065   4.248 2.58e-05 ***
## category_code_LT01_5_count   0.95832    0.06333  15.131  < 2e-16 ***
## category_code_LT01_8_count  -0.12731    0.27777  -0.458    0.647    
## category_code_LT01_9_count   0.33645    0.23127   1.455    0.146    
## category_code_LT01_14_count  0.34307    0.32962   1.041    0.298    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.617,  Adjusted R-squared:  0.6123 
## F-statistic: 131.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 0.611461752641505 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0274 -0.7657  0.0253  0.8794  3.8281 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97282    0.08868 112.456  < 2e-16 ***
## category_code_LT01_2_count   0.81375    0.07710  10.554  < 2e-16 ***
## category_code_LT01_3_count   0.46709    0.11197   4.171 3.58e-05 ***
## category_code_LT01_5_count   0.96617    0.06298  15.342  < 2e-16 ***
## category_code_LT01_8_count  -0.12301    0.27805  -0.442    0.658    
## category_code_LT01_9_count   0.35514    0.23108   1.537    0.125    
## category_code_LT01_15_count  0.07425    0.76593   0.097    0.923    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6162, Adjusted R-squared:  0.6115 
## F-statistic: 131.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 0.611514054075749 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0267 -0.7631  0.0260  0.8706  3.8287 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97225    0.08869 112.437  < 2e-16 ***
## category_code_LT01_2_count   0.81568    0.07701  10.592  < 2e-16 ***
## category_code_LT01_3_count   0.47106    0.11110   4.240 2.67e-05 ***
## category_code_LT01_5_count   0.96601    0.06296  15.343  < 2e-16 ***
## category_code_LT01_8_count  -0.11909    0.27833  -0.428    0.669    
## category_code_LT01_9_count   0.35511    0.23090   1.538    0.125    
## category_code_LT01_16_count -0.32740    1.19151  -0.275    0.784    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6162, Adjusted R-squared:  0.6115 
## F-statistic: 131.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 0.618516428952513 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0196 -0.7597  0.0042  0.8353  4.0993 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97016    0.09107 109.475  < 2e-16 ***
## category_code_LT01_2_count   0.66707    0.08977   7.431 4.82e-13 ***
## category_code_LT01_3_count   0.37036    0.11523   3.214 0.001395 ** 
## category_code_LT01_5_count   0.95883    0.06239  15.369  < 2e-16 ***
## category_code_LT01_8_count  -0.09486    0.27546  -0.344 0.730732    
## category_code_LT01_10_count  0.07560    0.11448   0.660 0.509322    
## category_code_LT01_11_count  0.38885    0.11703   3.323 0.000958 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6231, Adjusted R-squared:  0.6185 
## F-statistic: 135.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 0.61005404553441 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0173 -0.7530  0.0156  0.8401  3.8411 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95981    0.09202 108.232  < 2e-16 ***
## category_code_LT01_2_count   0.82229    0.07797  10.547  < 2e-16 ***
## category_code_LT01_3_count   0.47815    0.11181   4.276 2.28e-05 ***
## category_code_LT01_5_count   0.97030    0.06321  15.351  < 2e-16 ***
## category_code_LT01_8_count  -0.11650    0.27864  -0.418    0.676    
## category_code_LT01_10_count  0.07523    0.11579   0.650    0.516    
## category_code_LT01_12_count  0.08011    0.20987   0.382    0.703    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6148, Adjusted R-squared:  0.6101 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 0.610415695707282 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0172 -0.7605  0.0168  0.8433  3.8412 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95977    0.09198 108.282  < 2e-16 ***
## category_code_LT01_2_count   0.82143    0.07683  10.691  < 2e-16 ***
## category_code_LT01_3_count   0.47780    0.11155   4.283 2.21e-05 ***
## category_code_LT01_5_count   0.97030    0.06297  15.408  < 2e-16 ***
## category_code_LT01_8_count  -0.10028    0.27877  -0.360    0.719    
## category_code_LT01_10_count  0.07401    0.11573   0.639    0.523    
## category_code_LT01_13_count  0.19128    0.24660   0.776    0.438    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6151, Adjusted R-squared:  0.6104 
## F-statistic: 130.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 0.610776523485523 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0222 -0.7584  0.0311  0.8487  3.8321 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96889    0.09237 107.926  < 2e-16 ***
## category_code_LT01_2_count   0.81520    0.07734  10.540  < 2e-16 ***
## category_code_LT01_3_count   0.48607    0.11150   4.359 1.59e-05 ***
## category_code_LT01_5_count   0.96436    0.06338  15.216  < 2e-16 ***
## category_code_LT01_8_count  -0.11658    0.27822  -0.419    0.675    
## category_code_LT01_10_count  0.04945    0.11858   0.417    0.677    
## category_code_LT01_14_count  0.34732    0.33776   1.028    0.304    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6155, Adjusted R-squared:  0.6108 
## F-statistic:   131 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 0.609938336555081 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0187 -0.7557  0.0213  0.8354  3.8412 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.959725   0.092063 108.184  < 2e-16 ***
## category_code_LT01_2_count   0.828331   0.076544  10.822  < 2e-16 ***
## category_code_LT01_3_count   0.481308   0.112474   4.279 2.25e-05 ***
## category_code_LT01_5_count   0.972519   0.062963  15.446  < 2e-16 ***
## category_code_LT01_8_count  -0.112535   0.278502  -0.404    0.686    
## category_code_LT01_10_count  0.076493   0.115960   0.660    0.510    
## category_code_LT01_15_count -0.002564   0.768147  -0.003    0.997    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6146, Adjusted R-squared:  0.6099 
## F-statistic: 130.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 0.609994831719513 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0181 -0.7487  0.0125  0.8359  3.8418 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95912    0.09206 108.183  < 2e-16 ***
## category_code_LT01_2_count   0.82962    0.07652  10.842  < 2e-16 ***
## category_code_LT01_3_count   0.48353    0.11184   4.323 1.86e-05 ***
## category_code_LT01_5_count   0.97249    0.06294  15.450  < 2e-16 ***
## category_code_LT01_8_count  -0.10902    0.27879  -0.391    0.696    
## category_code_LT01_10_count  0.07709    0.11577   0.666    0.506    
## category_code_LT01_16_count -0.31845    1.19397  -0.267    0.790    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6147, Adjusted R-squared:   0.61 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 0.618305517017228 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0372 -0.7590 -0.0109  0.8140  4.0557 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98638    0.08794 113.562  < 2e-16 ***
## category_code_LT01_2_count   0.67315    0.08965   7.509 2.84e-13 ***
## category_code_LT01_3_count   0.38374    0.11354   3.380 0.000783 ***
## category_code_LT01_5_count   0.96080    0.06260  15.349  < 2e-16 ***
## category_code_LT01_8_count  -0.08627    0.27575  -0.313 0.754529    
## category_code_LT01_11_count  0.40078    0.12059   3.324 0.000955 ***
## category_code_LT01_12_count -0.08673    0.21381  -0.406 0.685183    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6229, Adjusted R-squared:  0.6183 
## F-statistic: 135.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 0.618442408399854 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0338 -0.7721 -0.0043  0.8272  4.0693 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98541    0.08792 113.578  < 2e-16 ***
## category_code_LT01_2_count   0.66805    0.08972   7.446 4.36e-13 ***
## category_code_LT01_3_count   0.38189    0.11355   3.363 0.000831 ***
## category_code_LT01_5_count   0.95731    0.06245  15.330  < 2e-16 ***
## category_code_LT01_8_count  -0.08230    0.27585  -0.298 0.765575    
## category_code_LT01_11_count  0.38451    0.11729   3.278 0.001119 ** 
## category_code_LT01_13_count  0.14272    0.24449   0.584 0.559659    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.623,  Adjusted R-squared:  0.6184 
## F-statistic: 135.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 0.618900875616077 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0334 -0.7641  0.0064  0.8209  4.0768 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98892    0.08792 113.618  < 2e-16 ***
## category_code_LT01_2_count   0.66088    0.09015   7.331 9.46e-13 ***
## category_code_LT01_3_count   0.38551    0.11347   3.398 0.000735 ***
## category_code_LT01_5_count   0.95164    0.06280  15.154  < 2e-16 ***
## category_code_LT01_8_count  -0.09632    0.27532  -0.350 0.726617    
## category_code_LT01_11_count  0.38230    0.11718   3.263 0.001181 ** 
## category_code_LT01_14_count  0.31517    0.32649   0.965 0.334858    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 0.618181502448595 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0352 -0.7682 -0.0035  0.8210  4.0584 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98583    0.08795 113.545  < 2e-16 ***
## category_code_LT01_2_count   0.67171    0.08965   7.492 3.18e-13 ***
## category_code_LT01_3_count   0.38452    0.11448   3.359 0.000843 ***
## category_code_LT01_5_count   0.95870    0.06243  15.356  < 2e-16 ***
## category_code_LT01_8_count  -0.09095    0.27554  -0.330 0.741487    
## category_code_LT01_11_count  0.38930    0.11714   3.323 0.000956 ***
## category_code_LT01_15_count -0.05375    0.75906  -0.071 0.943576    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6228, Adjusted R-squared:  0.6182 
## F-statistic: 135.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 0.618187084364546 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0352 -0.7681 -0.0068  0.8197  4.0574 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98567    0.08796 113.521  < 2e-16 ***
## category_code_LT01_2_count   0.67221    0.08985   7.482 3.41e-13 ***
## category_code_LT01_3_count   0.38463    0.11402   3.373 0.000801 ***
## category_code_LT01_5_count   0.95881    0.06242  15.362  < 2e-16 ***
## category_code_LT01_8_count  -0.08972    0.27583  -0.325 0.745124    
## category_code_LT01_11_count  0.38846    0.11719   3.315 0.000985 ***
## category_code_LT01_16_count -0.13055    1.18226  -0.110 0.912121    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6228, Adjusted R-squared:  0.6182 
## F-statistic: 135.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 0.610203694173807 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0309 -0.7645  0.0095  0.8793  3.8260 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97498    0.08881 112.323  < 2e-16 ***
## category_code_LT01_2_count   0.81970    0.07817  10.486  < 2e-16 ***
## category_code_LT01_3_count   0.48739    0.11010   4.427 1.18e-05 ***
## category_code_LT01_5_count   0.96807    0.06325  15.305  < 2e-16 ***
## category_code_LT01_8_count  -0.10052    0.27900  -0.360    0.719    
## category_code_LT01_12_count  0.07899    0.20984   0.376    0.707    
## category_code_LT01_13_count  0.19280    0.24669   0.782    0.435    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6149, Adjusted R-squared:  0.6102 
## F-statistic: 130.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 0.610714549479067 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0310 -0.7688  0.0154  0.8377  3.8217 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97926    0.08881 112.365  < 2e-16 ***
## category_code_LT01_2_count   0.81217    0.07868  10.323  < 2e-16 ***
## category_code_LT01_3_count   0.49199    0.10992   4.476 9.47e-06 ***
## category_code_LT01_5_count   0.96200    0.06357  15.132  < 2e-16 ***
## category_code_LT01_8_count  -0.11778    0.27839  -0.423    0.672    
## category_code_LT01_12_count  0.06506    0.21028   0.309    0.757    
## category_code_LT01_14_count  0.37034    0.33046   1.121    0.263    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6154, Adjusted R-squared:  0.6107 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 0.609720461425417 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0329 -0.7650  0.0045  0.8610  3.8255 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97549    0.08886 112.258  < 2e-16 ***
## category_code_LT01_2_count   0.82613    0.07798  10.594  < 2e-16 ***
## category_code_LT01_3_count   0.49036    0.11122   4.409 1.28e-05 ***
## category_code_LT01_5_count   0.97024    0.06325  15.341  < 2e-16 ***
## category_code_LT01_8_count  -0.11315    0.27873  -0.406    0.685    
## category_code_LT01_12_count  0.08419    0.20995   0.401    0.689    
## category_code_LT01_15_count  0.03560    0.76731   0.046    0.963    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6097 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 0.609765337109704 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0324 -0.7646 -0.0028  0.8586  3.8259 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97502    0.08887 112.241  < 2e-16 ***
## category_code_LT01_2_count   0.82774    0.07793  10.621  < 2e-16 ***
## category_code_LT01_3_count   0.49332    0.11044   4.467 9.85e-06 ***
## category_code_LT01_5_count   0.97019    0.06323  15.344  < 2e-16 ***
## category_code_LT01_8_count  -0.10971    0.27903  -0.393    0.694    
## category_code_LT01_12_count  0.08250    0.20995   0.393    0.695    
## category_code_LT01_16_count -0.28921    1.19455  -0.242    0.809    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6098 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 0.611122043700035 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0303 -0.7685  0.0222  0.8716  3.8220 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97898    0.08876 112.422  < 2e-16 ***
## category_code_LT01_2_count   0.80982    0.07773  10.419  < 2e-16 ***
## category_code_LT01_3_count   0.49079    0.10963   4.477 9.43e-06 ***
## category_code_LT01_5_count   0.96145    0.06339  15.168  < 2e-16 ***
## category_code_LT01_8_count  -0.10238    0.27850  -0.368    0.713    
## category_code_LT01_13_count  0.19242    0.24630   0.781    0.435    
## category_code_LT01_14_count  0.37562    0.32924   1.141    0.254    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6158, Adjusted R-squared:  0.6111 
## F-statistic: 131.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 0.610096991122711 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0327 -0.7742  0.0102  0.8858  3.8257 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97521    0.08882 112.308  < 2e-16 ***
## category_code_LT01_2_count   0.82507    0.07684  10.738  < 2e-16 ***
## category_code_LT01_3_count   0.48925    0.11095   4.410 1.27e-05 ***
## category_code_LT01_5_count   0.97034    0.06301  15.399  < 2e-16 ***
## category_code_LT01_8_count  -0.09653    0.27882  -0.346    0.729    
## category_code_LT01_13_count  0.19692    0.24709   0.797    0.426    
## category_code_LT01_15_count  0.06551    0.76816   0.085    0.932    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6148, Adjusted R-squared:  0.6101 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 0.610129242729328 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0322 -0.7643  0.0087  0.8804  3.8262 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97476    0.08883 112.289  < 2e-16 ***
## category_code_LT01_2_count   0.82679    0.07678  10.769  < 2e-16 ***
## category_code_LT01_3_count   0.49262    0.11015   4.472 9.63e-06 ***
## category_code_LT01_5_count   0.97024    0.06300  15.401  < 2e-16 ***
## category_code_LT01_8_count  -0.09362    0.27909  -0.335    0.737    
## category_code_LT01_13_count  0.19323    0.24684   0.783    0.434    
## category_code_LT01_16_count -0.26144    1.19467  -0.219    0.827    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6148, Adjusted R-squared:  0.6101 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 0.610638779660625 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0323 -0.7691  0.0206  0.8478  3.8215 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.979499   0.088820 112.357  < 2e-16 ***
## category_code_LT01_2_count   0.816707   0.077448  10.545  < 2e-16 ***
## category_code_LT01_3_count   0.494506   0.110708   4.467 9.87e-06 ***
## category_code_LT01_5_count   0.963636   0.063384  15.203  < 2e-16 ***
## category_code_LT01_8_count  -0.114671   0.278243  -0.412    0.680    
## category_code_LT01_14_count  0.378446   0.329494   1.149    0.251    
## category_code_LT01_15_count  0.009439   0.766285   0.012    0.990    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6106 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 0.610665708514393 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0320 -0.7687  0.0170  0.8435  3.8218 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97912    0.08884 112.332  < 2e-16 ***
## category_code_LT01_2_count   0.81786    0.07749  10.555  < 2e-16 ***
## category_code_LT01_3_count   0.49635    0.10995   4.514 7.95e-06 ***
## category_code_LT01_5_count   0.96368    0.06336  15.209  < 2e-16 ***
## category_code_LT01_8_count  -0.11212    0.27856  -0.402    0.687    
## category_code_LT01_14_count  0.37486    0.33001   1.136    0.257    
## category_code_LT01_16_count -0.22069    1.19487  -0.185    0.854    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6154, Adjusted R-squared:  0.6107 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 0.60964303058453 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0342 -0.7648  0.0046  0.8588  3.8258 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97520    0.08889 112.221  < 2e-16 ***
## category_code_LT01_2_count   0.83394    0.07649  10.903  < 2e-16 ***
## category_code_LT01_3_count   0.49648    0.11128   4.462 1.01e-05 ***
## category_code_LT01_5_count   0.97251    0.06299  15.440  < 2e-16 ***
## category_code_LT01_8_count  -0.10550    0.27888  -0.378    0.705    
## category_code_LT01_15_count  0.01739    0.76810   0.023    0.982    
## category_code_LT01_16_count -0.30102    1.19582  -0.252    0.801    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6096 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.619854003878213 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0129 -0.7593  0.0318  0.8244  4.1489 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96976    0.09089 109.695  < 2e-16 ***
## category_code_LT01_2_count   0.65391    0.09011   7.257 1.56e-12 ***
## category_code_LT01_3_count   0.35050    0.11579   3.027   0.0026 ** 
## category_code_LT01_5_count   0.94963    0.06169  15.394  < 2e-16 ***
## category_code_LT01_9_count   0.31189    0.22951   1.359   0.1748    
## category_code_LT01_10_count  0.05955    0.11480   0.519   0.6042    
## category_code_LT01_11_count  0.38383    0.11688   3.284   0.0011 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6244, Adjusted R-squared:  0.6199 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 0.611614131631195 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0095 -0.7490  0.0333  0.8887  3.8415 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95941    0.09181 108.478  < 2e-16 ***
## category_code_LT01_2_count   0.80585    0.07865  10.246  < 2e-16 ***
## category_code_LT01_3_count   0.45489    0.11257   4.041 6.18e-05 ***
## category_code_LT01_5_count   0.95970    0.06254  15.344  < 2e-16 ***
## category_code_LT01_9_count   0.33976    0.23184   1.466    0.143    
## category_code_LT01_10_count  0.05767    0.11609   0.497    0.620    
## category_code_LT01_12_count  0.07807    0.20930   0.373    0.709    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6163, Adjusted R-squared:  0.6116 
## F-statistic: 131.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 0.612139821803813 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0096 -0.7491  0.0347  0.8949  3.8414 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95955    0.09175 108.553  < 2e-16 ***
## category_code_LT01_2_count   0.80309    0.07760  10.349  < 2e-16 ***
## category_code_LT01_3_count   0.45325    0.11231   4.036 6.32e-05 ***
## category_code_LT01_5_count   0.95966    0.06225  15.416  < 2e-16 ***
## category_code_LT01_9_count   0.35308    0.23218   1.521    0.129    
## category_code_LT01_10_count  0.05553    0.11602   0.479    0.632    
## category_code_LT01_13_count  0.22086    0.24619   0.897    0.370    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6168, Adjusted R-squared:  0.6121 
## F-statistic: 131.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 0.612210957099664 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0143 -0.7573  0.0314  0.8856  3.8332 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96774    0.09217 108.151  < 2e-16 ***
## category_code_LT01_2_count   0.80026    0.07794  10.268  < 2e-16 ***
## category_code_LT01_3_count   0.46314    0.11231   4.124 4.38e-05 ***
## category_code_LT01_5_count   0.95461    0.06268  15.230  < 2e-16 ***
## category_code_LT01_9_count   0.32748    0.23200   1.412    0.159    
## category_code_LT01_10_count  0.03463    0.11876   0.292    0.771    
## category_code_LT01_14_count  0.31939    0.33761   0.946    0.345    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6169, Adjusted R-squared:  0.6122 
## F-statistic: 131.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 0.611506955291108 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0112 -0.7525  0.0364  0.8747  3.8415 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95950    0.09185 108.433  < 2e-16 ***
## category_code_LT01_2_count   0.81138    0.07727  10.500  < 2e-16 ***
## category_code_LT01_3_count   0.45706    0.11331   4.034 6.37e-05 ***
## category_code_LT01_5_count   0.96208    0.06226  15.454  < 2e-16 ***
## category_code_LT01_9_count   0.34006    0.23211   1.465    0.144    
## category_code_LT01_10_count  0.05848    0.11629   0.503    0.615    
## category_code_LT01_15_count  0.04616    0.76737   0.060    0.952    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6162, Adjusted R-squared:  0.6115 
## F-statistic: 131.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 0.611577916451439 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0105 -0.7489  0.0296  0.8682  3.8423 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95871    0.09184 108.435  < 2e-16 ***
## category_code_LT01_2_count   0.81317    0.07720  10.534  < 2e-16 ***
## category_code_LT01_3_count   0.46056    0.11259   4.091 5.03e-05 ***
## category_code_LT01_5_count   0.96210    0.06224  15.458  < 2e-16 ***
## category_code_LT01_9_count   0.34035    0.23186   1.468    0.143    
## category_code_LT01_10_count  0.05962    0.11607   0.514    0.608    
## category_code_LT01_16_count -0.36362    1.19031  -0.305    0.760    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6163, Adjusted R-squared:  0.6116 
## F-statistic: 131.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.619773368699171 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0272 -0.7721  0.0180  0.8183  4.1153 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98262    0.08775 113.758  < 2e-16 ***
## category_code_LT01_2_count   0.65861    0.09005   7.314 1.07e-12 ***
## category_code_LT01_3_count   0.36047    0.11432   3.153  0.00171 ** 
## category_code_LT01_5_count   0.95168    0.06193  15.367  < 2e-16 ***
## category_code_LT01_9_count   0.32257    0.22845   1.412  0.15858    
## category_code_LT01_11_count  0.39543    0.12039   3.285  0.00109 ** 
## category_code_LT01_12_count -0.08658    0.21321  -0.406  0.68485    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6244, Adjusted R-squared:  0.6198 
## F-statistic:   136 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.62002088411781 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0234 -0.7711  0.0237  0.8213  4.1325 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98151    0.08772 113.792  < 2e-16 ***
## category_code_LT01_2_count   0.65238    0.09014   7.237 1.78e-12 ***
## category_code_LT01_3_count   0.35761    0.11434   3.128  0.00187 ** 
## category_code_LT01_5_count   0.94788    0.06172  15.358  < 2e-16 ***
## category_code_LT01_9_count   0.33393    0.22885   1.459  0.14517    
## category_code_LT01_11_count  0.37807    0.11714   3.228  0.00133 ** 
## category_code_LT01_13_count  0.16999    0.24414   0.696  0.48656    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:   0.62 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.620217598622894 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0235 -0.7702  0.0300  0.8158  4.1325 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98485    0.08775 113.786  < 2e-16 ***
## category_code_LT01_2_count   0.64805    0.09047   7.163 2.91e-12 ***
## category_code_LT01_3_count   0.36279    0.11429   3.174  0.00160 ** 
## category_code_LT01_5_count   0.94322    0.06209  15.191  < 2e-16 ***
## category_code_LT01_9_count   0.30925    0.22891   1.351  0.17733    
## category_code_LT01_11_count  0.37804    0.11701   3.231  0.00132 ** 
## category_code_LT01_14_count  0.28095    0.32672   0.860  0.39027    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6248, Adjusted R-squared:  0.6202 
## F-statistic: 136.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.61964587669216 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0251 -0.7716  0.0184  0.8138  4.1195 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98206    0.08776 113.744  < 2e-16 ***
## category_code_LT01_2_count   0.65690    0.09007   7.293 1.22e-12 ***
## category_code_LT01_3_count   0.36034    0.11534   3.124  0.00189 ** 
## category_code_LT01_5_count   0.94948    0.06172  15.384  < 2e-16 ***
## category_code_LT01_9_count   0.32337    0.22867   1.414  0.15796    
## category_code_LT01_11_count  0.38379    0.11698   3.281  0.00111 ** 
## category_code_LT01_15_count -0.01256    0.75820  -0.017  0.98679    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6242, Adjusted R-squared:  0.6196 
## F-statistic: 135.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.619663085724952 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0249 -0.7714  0.0182  0.8131  4.1164 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98179    0.08777 113.722  < 2e-16 ***
## category_code_LT01_2_count   0.65787    0.09023   7.291 1.24e-12 ***
## category_code_LT01_3_count   0.36162    0.11479   3.150  0.00173 ** 
## category_code_LT01_5_count   0.94956    0.06171  15.389  < 2e-16 ***
## category_code_LT01_9_count   0.32410    0.22851   1.418  0.15673    
## category_code_LT01_11_count  0.38293    0.11703   3.272  0.00114 ** 
## category_code_LT01_16_count -0.17679    1.17884  -0.150  0.88085    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6243, Adjusted R-squared:  0.6197 
## F-statistic:   136 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 0.612062650957824 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0192 -0.7727  0.0186  0.9020  3.8301 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97082    0.08857 112.573  < 2e-16 ***
## category_code_LT01_2_count   0.79995    0.07899  10.127  < 2e-16 ***
## category_code_LT01_3_count   0.45893    0.11114   4.129 4.28e-05 ***
## category_code_LT01_5_count   0.95728    0.06255  15.303  < 2e-16 ***
## category_code_LT01_9_count   0.36409    0.23105   1.576    0.116    
## category_code_LT01_12_count  0.07581    0.20918   0.362    0.717    
## category_code_LT01_13_count  0.22220    0.24618   0.903    0.367    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6167, Adjusted R-squared:  0.6121 
## F-statistic: 131.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 0.612217351117435 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0198 -0.7644  0.0235  0.8718  3.8261 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97486    0.08862 112.555  < 2e-16 ***
## category_code_LT01_2_count   0.79654    0.07930  10.045  < 2e-16 ***
## category_code_LT01_3_count   0.46605    0.11099   4.199 3.19e-05 ***
## category_code_LT01_5_count   0.95234    0.06290  15.141  < 2e-16 ***
## category_code_LT01_9_count   0.33363    0.23119   1.443    0.150    
## category_code_LT01_12_count  0.06400    0.20974   0.305    0.760    
## category_code_LT01_14_count  0.33250    0.33071   1.005    0.315    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6169, Adjusted R-squared:  0.6122 
## F-statistic: 131.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 0.611427284518661 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0214 -0.7668  0.0304  0.8668  3.8296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97140    0.08865 112.486  < 2e-16 ***
## category_code_LT01_2_count   0.80774    0.07877  10.255  < 2e-16 ***
## category_code_LT01_3_count   0.46231    0.11233   4.116 4.53e-05 ***
## category_code_LT01_5_count   0.95958    0.06257  15.337  < 2e-16 ***
## category_code_LT01_9_count   0.35196    0.23096   1.524    0.128    
## category_code_LT01_12_count  0.08165    0.20934   0.390    0.697    
## category_code_LT01_15_count  0.07858    0.76619   0.103    0.918    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6161, Adjusted R-squared:  0.6114 
## F-statistic: 131.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 0.61148336746388 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0209 -0.7604  0.0286  0.8729  3.8301 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97085    0.08865 112.472  < 2e-16 ***
## category_code_LT01_2_count   0.80991    0.07867  10.295  < 2e-16 ***
## category_code_LT01_3_count   0.46659    0.11145   4.187 3.36e-05 ***
## category_code_LT01_5_count   0.95960    0.06256  15.340  < 2e-16 ***
## category_code_LT01_9_count   0.35202    0.23079   1.525    0.128    
## category_code_LT01_12_count  0.07951    0.20932   0.380    0.704    
## category_code_LT01_16_count -0.33969    1.19063  -0.285    0.776    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6162, Adjusted R-squared:  0.6115 
## F-statistic: 131.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 0.612780472949136 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0192 -0.7709  0.0233  0.8880  3.8264 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97456    0.08856 112.635  < 2e-16 ***
## category_code_LT01_2_count   0.79246    0.07842  10.105  < 2e-16 ***
## category_code_LT01_3_count   0.46350    0.11071   4.187 3.36e-05 ***
## category_code_LT01_5_count   0.95180    0.06265  15.192  < 2e-16 ***
## category_code_LT01_9_count   0.34635    0.23149   1.496    0.135    
## category_code_LT01_13_count  0.22092    0.24588   0.898    0.369    
## category_code_LT01_14_count  0.33623    0.32942   1.021    0.308    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6175, Adjusted R-squared:  0.6128 
## F-statistic: 132.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 0.611977236253908 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0212 -0.7743  0.0281  0.9063  3.8298 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97112    0.08858 112.563  < 2e-16 ***
## category_code_LT01_2_count   0.80460    0.07773  10.352  < 2e-16 ***
## category_code_LT01_3_count   0.45951    0.11208   4.100 4.84e-05 ***
## category_code_LT01_5_count   0.95964    0.06227  15.411  < 2e-16 ***
## category_code_LT01_9_count   0.36568    0.23129   1.581    0.115    
## category_code_LT01_13_count  0.22716    0.24664   0.921    0.357    
## category_code_LT01_15_count  0.11691    0.76703   0.152    0.879    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6167, Adjusted R-squared:  0.612 
## F-statistic: 131.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 0.612009972532536 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0206 -0.7610  0.0216  0.8948  3.8304 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97060    0.08859 112.545  < 2e-16 ***
## category_code_LT01_2_count   0.80697    0.07761  10.398  < 2e-16 ***
## category_code_LT01_3_count   0.46438    0.11118   4.177  3.5e-05 ***
## category_code_LT01_5_count   0.95959    0.06226  15.412  < 2e-16 ***
## category_code_LT01_9_count   0.36486    0.23108   1.579    0.115    
## category_code_LT01_13_count  0.22184    0.24636   0.900    0.368    
## category_code_LT01_16_count -0.30276    1.19065  -0.254    0.799    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6167, Adjusted R-squared:  0.612 
## F-statistic: 131.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 0.612147470861276 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0214 -0.7647  0.0224  0.8710  3.8258 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97516    0.08863 112.551  < 2e-16 ***
## category_code_LT01_2_count   0.80070    0.07811  10.251  < 2e-16 ***
## category_code_LT01_3_count   0.46767    0.11185   4.181 3.44e-05 ***
## category_code_LT01_5_count   0.95413    0.06267  15.225  < 2e-16 ***
## category_code_LT01_9_count   0.33377    0.23141   1.442    0.150    
## category_code_LT01_14_count  0.34015    0.32974   1.032    0.303    
## category_code_LT01_15_count  0.05205    0.76542   0.068    0.946    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6168, Adjusted R-squared:  0.6121 
## F-statistic: 131.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 0.61218687140288 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0210 -0.7642  0.0219  0.8646  3.8263 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97467    0.08864 112.528  < 2e-16 ***
## category_code_LT01_2_count   0.80241    0.07809  10.275  < 2e-16 ***
## category_code_LT01_3_count   0.47083    0.11098   4.242 2.64e-05 ***
## category_code_LT01_5_count   0.95421    0.06266  15.229  < 2e-16 ***
## category_code_LT01_9_count   0.33419    0.23124   1.445    0.149    
## category_code_LT01_14_count  0.33601    0.33024   1.017    0.309    
## category_code_LT01_16_count -0.27814    1.19133  -0.233    0.815    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6169, Adjusted R-squared:  0.6122 
## F-statistic: 131.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 0.611373948891376 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0228 -0.7717  0.0222  0.8790  3.8298 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97111    0.08867 112.456  < 2e-16 ***
## category_code_LT01_2_count   0.81552    0.07728  10.553  < 2e-16 ***
## category_code_LT01_3_count   0.46873    0.11237   4.171 3.58e-05 ***
## category_code_LT01_5_count   0.96204    0.06227  15.450  < 2e-16 ***
## category_code_LT01_9_count   0.35265    0.23100   1.527    0.127    
## category_code_LT01_15_count  0.05942    0.76692   0.077    0.938    
## category_code_LT01_16_count -0.34694    1.19187  -0.291    0.771    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6161, Adjusted R-squared:  0.6114 
## F-statistic: 131.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.618574047235468 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0185 -0.7592  0.0052  0.8350  4.0977 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96968    0.09104 109.507  < 2e-16 ***
## category_code_LT01_2_count   0.66864    0.08985   7.442 4.49e-13 ***
## category_code_LT01_3_count   0.36923    0.11517   3.206 0.001434 ** 
## category_code_LT01_5_count   0.95786    0.06187  15.482  < 2e-16 ***
## category_code_LT01_10_count  0.07626    0.11450   0.666 0.505695    
## category_code_LT01_11_count  0.40229    0.12050   3.339 0.000906 ***
## category_code_LT01_12_count -0.09379    0.21362  -0.439 0.660819    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6232, Adjusted R-squared:  0.6186 
## F-statistic: 135.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.618689489601193 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0157 -0.7589  0.0058  0.8301  4.1099 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96937    0.09102 109.523  < 2e-16 ***
## category_code_LT01_2_count   0.66360    0.08992   7.380  6.8e-13 ***
## category_code_LT01_3_count   0.36797    0.11517   3.195  0.00149 ** 
## category_code_LT01_5_count   0.95433    0.06166  15.476  < 2e-16 ***
## category_code_LT01_10_count  0.07305    0.11447   0.638  0.52368    
## category_code_LT01_11_count  0.38505    0.11724   3.284  0.00110 ** 
## category_code_LT01_13_count  0.14266    0.24412   0.584  0.55925    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6233, Adjusted R-squared:  0.6187 
## F-statistic: 135.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.618964571923137 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0193 -0.7636  0.0172  0.8257  4.1055 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97657    0.09140 109.155  < 2e-16 ***
## category_code_LT01_2_count   0.65874    0.09024   7.300 1.17e-12 ***
## category_code_LT01_3_count   0.37465    0.11530   3.249  0.00124 ** 
## category_code_LT01_5_count   0.94904    0.06210  15.283  < 2e-16 ***
## category_code_LT01_10_count  0.05305    0.11732   0.452  0.65133    
## category_code_LT01_11_count  0.38375    0.11715   3.276  0.00113 ** 
## category_code_LT01_14_count  0.27932    0.33477   0.834  0.40447    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6236, Adjusted R-squared:  0.619 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.618434214644894 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0162 -0.7587  0.0086  0.8367  4.0996 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96916    0.09108 109.456  < 2e-16 ***
## category_code_LT01_2_count   0.66725    0.08985   7.426 4.97e-13 ***
## category_code_LT01_3_count   0.37065    0.11596   3.196 0.001482 ** 
## category_code_LT01_5_count   0.95536    0.06167  15.492  < 2e-16 ***
## category_code_LT01_10_count  0.07556    0.11467   0.659 0.510239    
## category_code_LT01_11_count  0.39005    0.11708   3.332 0.000929 ***
## category_code_LT01_15_count -0.08585    0.76009  -0.113 0.910121    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.623,  Adjusted R-squared:  0.6184 
## F-statistic: 135.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.618439490955633 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0163 -0.7586  0.0024  0.8364  4.0986 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96907    0.09108 109.450  < 2e-16 ***
## category_code_LT01_2_count   0.66782    0.09005   7.416 5.33e-13 ***
## category_code_LT01_3_count   0.37055    0.11563   3.205 0.001440 ** 
## category_code_LT01_5_count   0.95559    0.06165  15.499  < 2e-16 ***
## category_code_LT01_10_count  0.07514    0.11449   0.656 0.511970    
## category_code_LT01_11_count  0.38890    0.11713   3.320 0.000967 ***
## category_code_LT01_16_count -0.16509    1.18083  -0.140 0.888870    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.623,  Adjusted R-squared:  0.6184 
## F-statistic: 135.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 0.610407477170961 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0125 -0.7492  0.0093  0.8721  3.8420 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95899    0.09195 108.306  < 2e-16 ***
## category_code_LT01_2_count   0.81599    0.07838  10.410  < 2e-16 ***
## category_code_LT01_3_count   0.47385    0.11180   4.238 2.69e-05 ***
## category_code_LT01_5_count   0.96467    0.06251  15.431  < 2e-16 ***
## category_code_LT01_10_count  0.07198    0.11575   0.622    0.534    
## category_code_LT01_12_count  0.07235    0.20970   0.345    0.730    
## category_code_LT01_13_count  0.19400    0.24630   0.788    0.431    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6151, Adjusted R-squared:  0.6104 
## F-statistic: 130.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 0.610703854414142 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0172 -0.7573  0.0225  0.8633  3.8332 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96771    0.09235 107.939  < 2e-16 ***
## category_code_LT01_2_count   0.81110    0.07875  10.299  < 2e-16 ***
## category_code_LT01_3_count   0.48231    0.11181   4.314 1.94e-05 ***
## category_code_LT01_5_count   0.95876    0.06292  15.239  < 2e-16 ***
## category_code_LT01_10_count  0.04824    0.11858   0.407    0.684    
## category_code_LT01_12_count  0.06087    0.21016   0.290    0.772    
## category_code_LT01_14_count  0.33784    0.33875   0.997    0.319    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6154, Adjusted R-squared:  0.6107 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 0.609915231794597 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0136 -0.7494  0.0082  0.8491  3.8421 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.958854   0.092036 108.206  < 2e-16 ***
## category_code_LT01_2_count  0.822630   0.078182  10.522  < 2e-16 ***
## category_code_LT01_3_count  0.476988   0.112776   4.229 2.79e-05 ***
## category_code_LT01_5_count  0.966370   0.062526  15.456  < 2e-16 ***
## category_code_LT01_10_count 0.074275   0.115994   0.640    0.522    
## category_code_LT01_12_count 0.076868   0.209845   0.366    0.714    
## category_code_LT01_15_count 0.002858   0.768455   0.004    0.997    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6146, Adjusted R-squared:  0.6099 
## F-statistic: 130.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 0.609975656365147 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0131 -0.7478  0.0078  0.8447  3.8427 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95825    0.09203 108.208  < 2e-16 ***
## category_code_LT01_2_count   0.82412    0.07815  10.545  < 2e-16 ***
## category_code_LT01_3_count   0.47949    0.11214   4.276 2.29e-05 ***
## category_code_LT01_5_count   0.96651    0.06251  15.461  < 2e-16 ***
## category_code_LT01_10_count  0.07500    0.11581   0.648    0.518    
## category_code_LT01_12_count  0.07529    0.20982   0.359    0.720    
## category_code_LT01_16_count -0.32909    1.19309  -0.276    0.783    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6147, Adjusted R-squared:   0.61 
## F-statistic: 130.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 0.611135883099342 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0173 -0.7575  0.0238  0.8654  3.8330 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96798    0.09229 108.004  < 2e-16 ***
## category_code_LT01_2_count   0.80840    0.07781  10.390  < 2e-16 ***
## category_code_LT01_3_count   0.48140    0.11150   4.318 1.91e-05 ***
## category_code_LT01_5_count   0.95857    0.06268  15.294  < 2e-16 ***
## category_code_LT01_10_count  0.04631    0.11855   0.391    0.696    
## category_code_LT01_13_count  0.19516    0.24598   0.793    0.428    
## category_code_LT01_14_count  0.34410    0.33758   1.019    0.309    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6158, Adjusted R-squared:  0.6111 
## F-statistic: 131.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 0.610314616098538 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0141 -0.7495  0.0167  0.8538  3.8419 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95904    0.09199 108.263  < 2e-16 ***
## category_code_LT01_2_count   0.82108    0.07706  10.655  < 2e-16 ***
## category_code_LT01_3_count   0.47599    0.11251   4.231 2.78e-05 ***
## category_code_LT01_5_count   0.96683    0.06223  15.536  < 2e-16 ***
## category_code_LT01_10_count  0.07278    0.11593   0.628    0.530    
## category_code_LT01_13_count  0.19702    0.24675   0.798    0.425    
## category_code_LT01_15_count  0.03453    0.76936   0.045    0.964    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.615,  Adjusted R-squared:  0.6103 
## F-statistic: 130.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 0.610362047262034 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0135 -0.7502  0.0152  0.8472  3.8426 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95840    0.09198 108.263  < 2e-16 ***
## category_code_LT01_2_count   0.82266    0.07702  10.681  < 2e-16 ***
## category_code_LT01_3_count   0.47886    0.11186   4.281 2.24e-05 ***
## category_code_LT01_5_count   0.96689    0.06222  15.540  < 2e-16 ***
## category_code_LT01_10_count  0.07374    0.11574   0.637    0.524    
## category_code_LT01_13_count  0.19343    0.24649   0.785    0.433    
## category_code_LT01_16_count -0.29663    1.19338  -0.249    0.804    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6151, Adjusted R-squared:  0.6104 
## F-statistic: 130.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 0.610637510151466 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0184 -0.7574  0.0160  0.8571  3.8331 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96784    0.09238 107.905  < 2e-16 ***
## category_code_LT01_2_count   0.81546    0.07752  10.519  < 2e-16 ***
## category_code_LT01_3_count   0.48502    0.11244   4.314 1.94e-05 ***
## category_code_LT01_5_count   0.96036    0.06269  15.320  < 2e-16 ***
## category_code_LT01_10_count  0.04872    0.11877   0.410    0.682    
## category_code_LT01_14_count  0.34536    0.33780   1.022    0.307    
## category_code_LT01_15_count -0.01107    0.76745  -0.014    0.988    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6106 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 0.610675459598627 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0180 -0.7568  0.0125  0.8548  3.8337 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96727    0.09239 107.884  < 2e-16 ***
## category_code_LT01_2_count   0.81664    0.07756  10.529  < 2e-16 ***
## category_code_LT01_3_count   0.48664    0.11179   4.353 1.63e-05 ***
## category_code_LT01_5_count   0.96057    0.06268  15.326  < 2e-16 ***
## category_code_LT01_10_count  0.04954    0.11865   0.418    0.676    
## category_code_LT01_14_count  0.34045    0.33850   1.006    0.315    
## category_code_LT01_16_count -0.26181    1.19416  -0.219    0.827    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6154, Adjusted R-squared:  0.6107 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609873740079438 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0145 -0.7477  0.0100  0.8392  3.8428 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95813    0.09207 108.159  < 2e-16 ***
## category_code_LT01_2_count   0.82994    0.07672  10.817  < 2e-16 ***
## category_code_LT01_3_count   0.48286    0.11284   4.279 2.26e-05 ***
## category_code_LT01_5_count   0.96870    0.06223  15.567  < 2e-16 ***
## category_code_LT01_10_count  0.07637    0.11598   0.658    0.511    
## category_code_LT01_15_count -0.01658    0.76921  -0.022    0.983    
## category_code_LT01_16_count -0.34192    1.19442  -0.286    0.775    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6146, Adjusted R-squared:  0.6099 
## F-statistic: 130.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.618515058920307 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0332 -0.7747 -0.0111  0.8193  4.0675 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98516    0.08788 113.628  < 2e-16 ***
## category_code_LT01_2_count   0.66952    0.08980   7.455 4.08e-13 ***
## category_code_LT01_3_count   0.38098    0.11347   3.358 0.000847 ***
## category_code_LT01_5_count   0.95667    0.06191  15.453  < 2e-16 ***
## category_code_LT01_11_count  0.39733    0.12074   3.291 0.001071 ** 
## category_code_LT01_12_count -0.09124    0.21357  -0.427 0.669398    
## category_code_LT01_13_count  0.14801    0.24412   0.606 0.544582    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6231, Adjusted R-squared:  0.6185 
## F-statistic: 135.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.618989953741453 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0325 -0.7745  0.0069  0.8127  4.0749 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98871    0.08788 113.667  < 2e-16 ***
## category_code_LT01_2_count   0.66240    0.09020   7.343 8.72e-13 ***
## category_code_LT01_3_count   0.38456    0.11339   3.392 0.000751 ***
## category_code_LT01_5_count   0.95068    0.06226  15.269  < 2e-16 ***
## category_code_LT01_11_count  0.39697    0.12053   3.294 0.001061 ** 
## category_code_LT01_12_count -0.10419    0.21392  -0.487 0.626452    
## category_code_LT01_14_count  0.32389    0.32716   0.990 0.322669    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6236, Adjusted R-squared:  0.619 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.618235609975859 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0342 -0.7698 -0.0103  0.8168  4.0562 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98550    0.08791 113.591  < 2e-16 ***
## category_code_LT01_2_count   0.67333    0.08975   7.502 2.97e-13 ***
## category_code_LT01_3_count   0.38381    0.11441   3.355 0.000856 ***
## category_code_LT01_5_count   0.95776    0.06191  15.470  < 2e-16 ***
## category_code_LT01_11_count  0.40230    0.12064   3.335 0.000919 ***
## category_code_LT01_12_count -0.09033    0.21376  -0.423 0.672805    
## category_code_LT01_15_count -0.06770    0.75945  -0.089 0.929005    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6228, Adjusted R-squared:  0.6182 
## F-statistic: 135.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.618243102191219 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0342 -0.7701 -0.0153  0.8156  4.0550 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98532    0.08792 113.569  < 2e-16 ***
## category_code_LT01_2_count   0.67392    0.08995   7.492 3.17e-13 ***
## category_code_LT01_3_count   0.38391    0.11396   3.369 0.000815 ***
## category_code_LT01_5_count   0.95795    0.06190  15.476  < 2e-16 ***
## category_code_LT01_11_count  0.40125    0.12064   3.326 0.000947 ***
## category_code_LT01_12_count -0.09010    0.21365  -0.422 0.673407    
## category_code_LT01_16_count -0.15660    1.18102  -0.133 0.894564    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6229, Adjusted R-squared:  0.6182 
## F-statistic: 135.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.619080992254827 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0289 -0.7730  0.0152  0.8157  4.0888 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98754    0.08785 113.682  < 2e-16 ***
## category_code_LT01_2_count   0.65731    0.09030   7.279 1.34e-12 ***
## category_code_LT01_3_count   0.38259    0.11340   3.374  0.00080 ***
## category_code_LT01_5_count   0.94715    0.06210  15.252  < 2e-16 ***
## category_code_LT01_11_count  0.37849    0.11738   3.224  0.00135 ** 
## category_code_LT01_13_count  0.14525    0.24392   0.595  0.55179    
## category_code_LT01_14_count  0.31172    0.32636   0.955  0.33998    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.6183741992766 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0310 -0.7741  0.0047  0.8323  4.0713 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98457    0.08788 113.611  < 2e-16 ***
## category_code_LT01_2_count   0.66787    0.08983   7.435 4.69e-13 ***
## category_code_LT01_3_count   0.38118    0.11444   3.331 0.000931 ***
## category_code_LT01_5_count   0.95436    0.06170  15.467  < 2e-16 ***
## category_code_LT01_11_count  0.38521    0.11737   3.282 0.001104 ** 
## category_code_LT01_13_count  0.14617    0.24466   0.597 0.550494    
## category_code_LT01_15_count -0.02666    0.76045  -0.035 0.972049    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.623,  Adjusted R-squared:  0.6184 
## F-statistic: 135.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.618380990745459 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0309 -0.7740  0.0034  0.8324  4.0697 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98442    0.08790 113.590  < 2e-16 ***
## category_code_LT01_2_count   0.66846    0.09003   7.425 5.02e-13 ***
## category_code_LT01_3_count   0.38172    0.11398   3.349 0.000873 ***
## category_code_LT01_5_count   0.95446    0.06169  15.471  < 2e-16 ***
## category_code_LT01_11_count  0.38457    0.11739   3.276 0.001128 ** 
## category_code_LT01_13_count  0.14567    0.24437   0.596 0.551385    
## category_code_LT01_16_count -0.11798    1.18177  -0.100 0.920516    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.623,  Adjusted R-squared:  0.6184 
## F-statistic: 135.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.618812466356322 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0300 -0.7751  0.0122  0.8224  4.0775 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98789    0.08789 113.647  < 2e-16 ***
## category_code_LT01_2_count   0.66102    0.09023   7.326 9.82e-13 ***
## category_code_LT01_3_count   0.38545    0.11434   3.371 0.000808 ***
## category_code_LT01_5_count   0.94819    0.06211  15.267  < 2e-16 ***
## category_code_LT01_11_count  0.38347    0.11722   3.271 0.001146 ** 
## category_code_LT01_14_count  0.31351    0.32652   0.960 0.337460    
## category_code_LT01_15_count -0.06982    0.75853  -0.092 0.926694    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6234, Adjusted R-squared:  0.6188 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.618809874437762 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0301 -0.7750  0.0116  0.8224  4.0779 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98781    0.08791 113.620  < 2e-16 ***
## category_code_LT01_2_count   0.66123    0.09049   7.307 1.11e-12 ***
## category_code_LT01_3_count   0.38485    0.11388   3.379 0.000784 ***
## category_code_LT01_5_count   0.94840    0.06210  15.273  < 2e-16 ***
## category_code_LT01_11_count  0.38279    0.11727   3.264 0.001174 ** 
## category_code_LT01_14_count  0.31162    0.32700   0.953 0.341071    
## category_code_LT01_16_count -0.08469    1.18190  -0.072 0.942902    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6234, Adjusted R-squared:  0.6188 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.618109852547518 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0319 -0.7738 -0.0031  0.8228  4.0579 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98470    0.08793 113.551  < 2e-16 ***
## category_code_LT01_2_count   0.67241    0.08996   7.474 3.59e-13 ***
## category_code_LT01_3_count   0.38471    0.11497   3.346 0.000882 ***
## category_code_LT01_5_count   0.95558    0.06169  15.489  < 2e-16 ***
## category_code_LT01_11_count  0.38940    0.11724   3.321 0.000962 ***
## category_code_LT01_15_count -0.06115    0.76001  -0.080 0.935905    
## category_code_LT01_16_count -0.15330    1.18250  -0.130 0.896906    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6227, Adjusted R-squared:  0.6181 
## F-statistic: 135.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.611073861310846 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0255 -0.7684  0.0080  0.8626  3.8233 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97770    0.08873 112.455  < 2e-16 ***
## category_code_LT01_2_count   0.80580    0.07909  10.188  < 2e-16 ***
## category_code_LT01_3_count   0.48708    0.10993   4.431 1.16e-05 ***
## category_code_LT01_5_count   0.95641    0.06290  15.206  < 2e-16 ***
## category_code_LT01_12_count  0.05728    0.21012   0.273    0.785    
## category_code_LT01_13_count  0.19570    0.24602   0.795    0.427    
## category_code_LT01_14_count  0.36609    0.33027   1.108    0.268    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6158, Adjusted R-squared:  0.6111 
## F-statistic: 131.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.610107395804311 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0276 -0.7636  0.0069  0.8886  3.8269 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97404    0.08878 112.351  < 2e-16 ***
## category_code_LT01_2_count   0.81918    0.07845  10.441  < 2e-16 ***
## category_code_LT01_3_count   0.48470    0.11126   4.356 1.61e-05 ***
## category_code_LT01_5_count   0.96473    0.06254  15.425  < 2e-16 ***
## category_code_LT01_12_count  0.07649    0.20977   0.365    0.716    
## category_code_LT01_13_count  0.19931    0.24679   0.808    0.420    
## category_code_LT01_15_count  0.07092    0.76838   0.092    0.926    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6148, Adjusted R-squared:  0.6101 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.610140939530825 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0272 -0.7632  0.0037  0.8820  3.8274 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97361    0.08878 112.336  < 2e-16 ***
## category_code_LT01_2_count   0.82110    0.07839  10.474  < 2e-16 ***
## category_code_LT01_3_count   0.48835    0.11047   4.421 1.21e-05 ***
## category_code_LT01_5_count   0.96477    0.06254  15.427  < 2e-16 ***
## category_code_LT01_12_count  0.07483    0.20976   0.357    0.721    
## category_code_LT01_13_count  0.19536    0.24656   0.792    0.429    
## category_code_LT01_16_count -0.26898    1.19379  -0.225    0.822    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6148, Adjusted R-squared:  0.6101 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.610572872949995 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0271 -0.7676  0.0113  0.8429  3.8229 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97808    0.08878 112.385  < 2e-16 ***
## category_code_LT01_2_count   0.81247    0.07889  10.298  < 2e-16 ***
## category_code_LT01_3_count   0.49044    0.11106   4.416 1.24e-05 ***
## category_code_LT01_5_count   0.95810    0.06292  15.228  < 2e-16 ***
## category_code_LT01_12_count  0.06192    0.21027   0.294    0.769    
## category_code_LT01_14_count  0.36808    0.33056   1.114    0.266    
## category_code_LT01_15_count  0.01296    0.76663   0.017    0.987    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6106 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.61060384852646 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0268 -0.7673  0.0084  0.8394  3.8233 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97770    0.08880 112.365  < 2e-16 ***
## category_code_LT01_2_count   0.81379    0.07892  10.311  < 2e-16 ***
## category_code_LT01_3_count   0.49255    0.11029   4.466  9.9e-06 ***
## category_code_LT01_5_count   0.95826    0.06291  15.233  < 2e-16 ***
## category_code_LT01_12_count  0.06092    0.21022   0.290    0.772    
## category_code_LT01_14_count  0.36444    0.33101   1.101    0.271    
## category_code_LT01_16_count -0.23679    1.19381  -0.198    0.843    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6106 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609643130680191 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0287 -0.7635 -0.0073  0.8682  3.8270 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97392    0.08884 112.264  < 2e-16 ***
## category_code_LT01_2_count   0.82795    0.07819  10.588  < 2e-16 ***
## category_code_LT01_3_count   0.49184    0.11165   4.405  1.3e-05 ***
## category_code_LT01_5_count   0.96653    0.06255  15.452  < 2e-16 ***
## category_code_LT01_12_count  0.07944    0.20990   0.378    0.705    
## category_code_LT01_15_count  0.02208    0.76835   0.029    0.977    
## category_code_LT01_16_count -0.31041    1.19488  -0.260    0.795    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6096 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.611017800216282 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0269 -0.7675  0.0134  0.8798  3.8230 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97796    0.08873 112.452  < 2e-16 ***
## category_code_LT01_2_count   0.80943    0.07796  10.383  < 2e-16 ***
## category_code_LT01_3_count   0.48850    0.11076   4.410 1.27e-05 ***
## category_code_LT01_5_count   0.95799    0.06268  15.285  < 2e-16 ***
## category_code_LT01_13_count  0.19844    0.24644   0.805    0.421    
## category_code_LT01_14_count  0.37292    0.32930   1.132    0.258    
## category_code_LT01_15_count  0.04557    0.76741   0.059    0.953    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6157, Adjusted R-squared:  0.611 
## F-statistic: 131.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.611037401218717 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0266 -0.7672  0.0130  0.8743  3.8233 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97761    0.08875 112.430  < 2e-16 ***
## category_code_LT01_2_count   0.81084    0.07799  10.397  < 2e-16 ***
## category_code_LT01_3_count   0.49102    0.10998   4.465 9.96e-06 ***
## category_code_LT01_5_count   0.95807    0.06267  15.288  < 2e-16 ***
## category_code_LT01_13_count  0.19562    0.24620   0.795    0.427    
## category_code_LT01_14_count  0.37007    0.32979   1.122    0.262    
## category_code_LT01_16_count -0.20077    1.19412  -0.168    0.867    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6157, Adjusted R-squared:  0.611 
## F-statistic: 131.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.61004387459047 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0290 -0.7634  0.0047  0.8886  3.8271 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97385    0.08880 112.322  < 2e-16 ***
## category_code_LT01_2_count   0.82629    0.07706  10.723  < 2e-16 ***
## category_code_LT01_3_count   0.49037    0.11136   4.403 1.31e-05 ***
## category_code_LT01_5_count   0.96704    0.06225  15.534  < 2e-16 ***
## category_code_LT01_13_count  0.19885    0.24703   0.805    0.421    
## category_code_LT01_15_count  0.05442    0.76930   0.071    0.944    
## category_code_LT01_16_count -0.27509    1.19528  -0.230    0.818    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6148, Adjusted R-squared:   0.61 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.610537249631333 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0281 -0.7675  0.0152  0.8497  3.8230 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.977931   0.088805 112.358  < 2e-16 ***
## category_code_LT01_2_count   0.818142   0.077699  10.530  < 2e-16 ***
## category_code_LT01_3_count   0.495202   0.111115   4.457 1.03e-05 ***
## category_code_LT01_5_count   0.959876   0.062682  15.313  < 2e-16 ***
## category_code_LT01_14_count  0.372057   0.330045   1.127    0.260    
## category_code_LT01_15_count -0.001216   0.767286  -0.002    0.999    
## category_code_LT01_16_count -0.244347   1.195085  -0.204    0.838    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6152, Adjusted R-squared:  0.6105 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 0.644560877493618 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9649 -0.7222  0.0358  0.8656  3.4877 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95288    0.08491 117.210  < 2e-16 ***
## category_code_LT01_2_count  0.46979    0.08987   5.228 2.54e-07 ***
## category_code_LT01_4_count  0.58492    0.09478   6.171 1.42e-09 ***
## category_code_LT01_5_count  0.90477    0.06094  14.847  < 2e-16 ***
## category_code_LT01_6_count  0.31776    0.14954   2.125  0.03409 *  
## category_code_LT01_7_count  0.40793    0.15038   2.713  0.00691 ** 
## category_code_LT01_8_count -0.16793    0.26613  -0.631  0.52832    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6489, Adjusted R-squared:  0.6446 
## F-statistic: 151.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 0.645499977164825 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9531 -0.7148  0.0105  0.8681  3.5039 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94853    0.08479 117.331  < 2e-16 ***
## category_code_LT01_2_count  0.45746    0.09032   5.065 5.79e-07 ***
## category_code_LT01_4_count  0.57814    0.09478   6.100 2.15e-09 ***
## category_code_LT01_5_count  0.89397    0.06036  14.811  < 2e-16 ***
## category_code_LT01_6_count  0.30544    0.14935   2.045   0.0414 *  
## category_code_LT01_7_count  0.38651    0.15075   2.564   0.0106 *  
## category_code_LT01_9_count  0.28657    0.21979   1.304   0.1929    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.341 on 491 degrees of freedom
## Multiple R-squared:  0.6498, Adjusted R-squared:  0.6455 
## F-statistic: 151.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 0.644426475001558 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9490 -0.7126  0.0268  0.8758  3.4498 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94067    0.08795 113.023  < 2e-16 ***
## category_code_LT01_2_count   0.46844    0.09002   5.204 2.88e-07 ***
## category_code_LT01_4_count   0.58361    0.09482   6.155 1.56e-09 ***
## category_code_LT01_5_count   0.89938    0.06031  14.912  < 2e-16 ***
## category_code_LT01_6_count   0.30329    0.15117   2.006  0.04537 *  
## category_code_LT01_7_count   0.39941    0.15077   2.649  0.00833 ** 
## category_code_LT01_10_count  0.05094    0.11052   0.461  0.64507    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6487, Adjusted R-squared:  0.6444 
## F-statistic: 151.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~ new_category_count_col 0.700607290769089 
## 
## Call:
## lm(formula = single.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.7965 -0.6888  0.0159  0.7176  3.8799 
## 
## Coefficients:
##                        Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             9.49821    0.08327  114.07   <2e-16 ***
## new_category_count_col  1.31774    0.03862   34.12   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.232 on 496 degrees of freedom
## Multiple R-squared:  0.7012, Adjusted R-squared:  0.7006 
## F-statistic:  1164 on 1 and 496 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 0.64547532043629 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9638 -0.7383  0.0018  0.8738  3.4914 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95634    0.08486 117.329  < 2e-16 ***
## category_code_LT01_2_count   0.42845    0.09556   4.483 9.15e-06 ***
## category_code_LT01_4_count   0.54861    0.09866   5.560 4.43e-08 ***
## category_code_LT01_5_count   0.89823    0.06023  14.914  < 2e-16 ***
## category_code_LT01_6_count   0.29145    0.15022   1.940   0.0529 .  
## category_code_LT01_7_count   0.35991    0.15407   2.336   0.0199 *  
## category_code_LT01_11_count  0.15388    0.11923   1.291   0.1974    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.341 on 491 degrees of freedom
## Multiple R-squared:  0.6498, Adjusted R-squared:  0.6455 
## F-statistic: 151.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 0.644279970061448 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9598 -0.7166  0.0153  0.8643  3.4948 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95128    0.08491 117.198  < 2e-16 ***
## category_code_LT01_2_count   0.47197    0.09055   5.212 2.76e-07 ***
## category_code_LT01_4_count   0.58516    0.09502   6.158 1.53e-09 ***
## category_code_LT01_5_count   0.89972    0.06053  14.864  < 2e-16 ***
## category_code_LT01_6_count   0.31528    0.15020   2.099  0.03632 *  
## category_code_LT01_7_count   0.40470    0.15036   2.692  0.00735 ** 
## category_code_LT01_12_count -0.02027    0.20135  -0.101  0.91986    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6486, Adjusted R-squared:  0.6443 
## F-statistic:   151 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 0.644273304628497 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9594 -0.7161  0.0179  0.8652  3.4954 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.951262   0.084911 117.196  < 2e-16 ***
## category_code_LT01_2_count  0.470765   0.089945   5.234 2.46e-07 ***
## category_code_LT01_4_count  0.584325   0.095059   6.147 1.64e-09 ***
## category_code_LT01_5_count  0.899179   0.060339  14.902  < 2e-16 ***
## category_code_LT01_6_count  0.313885   0.149499   2.100  0.03628 *  
## category_code_LT01_7_count  0.404197   0.151338   2.671  0.00782 ** 
## category_code_LT01_13_count 0.007257   0.237733   0.031  0.97566    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6486, Adjusted R-squared:  0.6443 
## F-statistic:   151 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 0.644293026795142 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9593 -0.7159  0.0198  0.8664  3.4960 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95185    0.08498 117.109  < 2e-16 ***
## category_code_LT01_2_count   0.46985    0.09009   5.216 2.71e-07 ***
## category_code_LT01_4_count   0.58231    0.09574   6.082 2.38e-09 ***
## category_code_LT01_5_count   0.89812    0.06068  14.802  < 2e-16 ***
## category_code_LT01_6_count   0.31636    0.15025   2.106   0.0357 *  
## category_code_LT01_7_count   0.40315    0.15065   2.676   0.0077 ** 
## category_code_LT01_14_count  0.05374    0.32025   0.168   0.8668    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6486, Adjusted R-squared:  0.6443 
## F-statistic:   151 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 0.644274016176178 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9595 -0.7163  0.0177  0.8651  3.4953 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95130    0.08491 117.194  < 2e-16 ***
## category_code_LT01_2_count   0.47063    0.09005   5.227 2.56e-07 ***
## category_code_LT01_4_count   0.58418    0.09515   6.140 1.71e-09 ***
## category_code_LT01_5_count   0.89927    0.06034  14.904  < 2e-16 ***
## category_code_LT01_6_count   0.31354    0.14959   2.096  0.03659 *  
## category_code_LT01_7_count   0.40495    0.15045   2.692  0.00735 ** 
## category_code_LT01_15_count  0.03188    0.72860   0.044  0.96512    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6486, Adjusted R-squared:  0.6443 
## F-statistic:   151 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 0.644536933454359 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9589 -0.7205  0.0204  0.8681  3.4964 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95161    0.08488 117.242  < 2e-16 ***
## category_code_LT01_2_count   0.46326    0.09073   5.106 4.71e-07 ***
## category_code_LT01_4_count   0.58513    0.09479   6.173 1.40e-09 ***
## category_code_LT01_5_count   0.89798    0.06034  14.882  < 2e-16 ***
## category_code_LT01_6_count   0.32220    0.15006   2.147  0.03227 *  
## category_code_LT01_7_count   0.40609    0.15032   2.702  0.00714 ** 
## category_code_LT01_16_count  0.68890    1.14015   0.604  0.54598    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.343 on 491 degrees of freedom
## Multiple R-squared:  0.6488, Adjusted R-squared:  0.6445 
## F-statistic: 151.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 0.641006717494333 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9610 -0.7424  0.0828  0.9138  3.4908 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.94779    0.08536 116.543  < 2e-16 ***
## category_code_LT01_2_count  0.48654    0.09013   5.398 1.05e-07 ***
## category_code_LT01_4_count  0.63847    0.09247   6.905 1.56e-11 ***
## category_code_LT01_5_count  0.90655    0.06131  14.787  < 2e-16 ***
## category_code_LT01_6_count  0.30191    0.15039   2.008   0.0452 *  
## category_code_LT01_8_count -0.15738    0.26745  -0.588   0.5565    
## category_code_LT01_9_count  0.34308    0.22035   1.557   0.1201    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6453, Adjusted R-squared:  0.641 
## F-statistic: 148.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 0.639564355585288 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9532 -0.7353  0.0890  0.8712  3.4143 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93543    0.08854 112.209  < 2e-16 ***
## category_code_LT01_2_count   0.50029    0.08979   5.571 4.17e-08 ***
## category_code_LT01_4_count   0.64694    0.09246   6.997 8.63e-12 ***
## category_code_LT01_5_count   0.91303    0.06130  14.895  < 2e-16 ***
## category_code_LT01_6_count   0.29611    0.15226   1.945   0.0524 .  
## category_code_LT01_8_count  -0.14674    0.26788  -0.548   0.5841    
## category_code_LT01_10_count  0.07441    0.11096   0.671   0.5028    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6439, Adjusted R-squared:  0.6396 
## F-statistic:   148 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 0.641712177997636 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9735 -0.7463  0.0509  0.8600  3.4770 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95810    0.08534 116.685  < 2e-16 ***
## category_code_LT01_2_count   0.43991    0.09594   4.585 5.76e-06 ***
## category_code_LT01_4_count   0.58925    0.09774   6.029 3.25e-09 ***
## category_code_LT01_5_count   0.90970    0.06114  14.880  < 2e-16 ***
## category_code_LT01_6_count   0.28064    0.15104   1.858   0.0638 .  
## category_code_LT01_8_count  -0.13161    0.26712  -0.493   0.6224    
## category_code_LT01_11_count  0.21525    0.11681   1.843   0.0660 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.646,  Adjusted R-squared:  0.6417 
## F-statistic: 149.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 0.639239721622827 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9687 -0.7404  0.0903  0.8924  3.4804 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95085    0.08554 116.323  < 2e-16 ***
## category_code_LT01_2_count   0.50546    0.09030   5.598 3.62e-08 ***
## category_code_LT01_4_count   0.65004    0.09263   7.018 7.54e-12 ***
## category_code_LT01_5_count   0.91325    0.06150  14.849  < 2e-16 ***
## category_code_LT01_6_count   0.31253    0.15135   2.065   0.0395 *  
## category_code_LT01_8_count  -0.14275    0.26812  -0.532   0.5947    
## category_code_LT01_12_count -0.01748    0.20289  -0.086   0.9314    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:  0.6392 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 0.63930207639438 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9679 -0.7403  0.0849  0.8807  3.4816 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95074    0.08554 116.331  < 2e-16 ***
## category_code_LT01_2_count   0.50310    0.08973   5.607 3.44e-08 ***
## category_code_LT01_4_count   0.64659    0.09291   6.959 1.10e-11 ***
## category_code_LT01_5_count   0.91221    0.06135  14.868  < 2e-16 ***
## category_code_LT01_6_count   0.31213    0.15065   2.072   0.0388 *  
## category_code_LT01_8_count  -0.13892    0.26837  -0.518   0.6049    
## category_code_LT01_13_count  0.07238    0.23822   0.304   0.7614    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 0.63932092649841 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9681 -0.7416  0.0917  0.8852  3.4821 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95208    0.08561 116.249  < 2e-16 ***
## category_code_LT01_2_count   0.50214    0.08987   5.588 3.82e-08 ***
## category_code_LT01_4_count   0.64443    0.09359   6.886 1.77e-11 ***
## category_code_LT01_5_count   0.91058    0.06167  14.766  < 2e-16 ***
## category_code_LT01_6_count   0.31664    0.15143   2.091    0.037 *  
## category_code_LT01_8_count  -0.14531    0.26798  -0.542    0.588    
## category_code_LT01_14_count  0.11057    0.32191   0.343    0.731    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 0.639235608302887 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9684 -0.7404  0.0909  0.8933  3.4809 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95083    0.08555 116.319  < 2e-16 ***
## category_code_LT01_2_count   0.50472    0.08975   5.624 3.14e-08 ***
## category_code_LT01_4_count   0.64981    0.09270   7.010 7.93e-12 ***
## category_code_LT01_5_count   0.91279    0.06134  14.881  < 2e-16 ***
## category_code_LT01_6_count   0.31153    0.15076   2.066   0.0393 *  
## category_code_LT01_8_count  -0.14342    0.26797  -0.535   0.5928    
## category_code_LT01_15_count -0.03136    0.73335  -0.043   0.9659    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:  0.6392 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 0.639489962011711 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9683 -0.7429  0.0847  0.8945  3.4814 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95126    0.08552 116.365  < 2e-16 ***
## category_code_LT01_2_count   0.49709    0.09046   5.495 6.28e-08 ***
## category_code_LT01_4_count   0.65036    0.09240   7.038 6.59e-12 ***
## category_code_LT01_5_count   0.91195    0.06132  14.872  < 2e-16 ***
## category_code_LT01_6_count   0.31973    0.15127   2.114    0.035 *  
## category_code_LT01_8_count  -0.15227    0.26827  -0.568    0.571    
## category_code_LT01_16_count  0.67855    1.14984   0.590    0.555    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6438, Adjusted R-squared:  0.6395 
## F-statistic: 147.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 0.64093096142006 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9449 -0.7427  0.0981  0.9045  3.4486 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93506    0.08835 112.448  < 2e-16 ***
## category_code_LT01_2_count   0.48506    0.09027   5.374 1.19e-07 ***
## category_code_LT01_4_count   0.63626    0.09252   6.877 1.87e-11 ***
## category_code_LT01_5_count   0.90166    0.06068  14.860  < 2e-16 ***
## category_code_LT01_6_count   0.28746    0.15190   1.892    0.059 .  
## category_code_LT01_9_count   0.32651    0.22165   1.473    0.141    
## category_code_LT01_10_count  0.05489    0.11144   0.493    0.623    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6453, Adjusted R-squared:  0.6409 
## F-statistic: 148.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 0.6430753432705 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9617 -0.7461  0.0868  0.8494  3.4932 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95365    0.08517 116.863  < 2e-16 ***
## category_code_LT01_2_count   0.42587    0.09625   4.424 1.19e-05 ***
## category_code_LT01_4_count   0.58006    0.09769   5.938 5.47e-09 ***
## category_code_LT01_5_count   0.89907    0.06051  14.859  < 2e-16 ***
## category_code_LT01_6_count   0.26948    0.15070   1.788   0.0744 .  
## category_code_LT01_9_count   0.32001    0.21984   1.456   0.1461    
## category_code_LT01_11_count  0.20854    0.11669   1.787   0.0745 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6474, Adjusted R-squared:  0.6431 
## F-statistic: 150.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 0.640761412779696 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9564 -0.7426  0.0861  0.9236  3.4974 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94635    0.08535 116.535  < 2e-16 ***
## category_code_LT01_2_count   0.48867    0.09082   5.380 1.15e-07 ***
## category_code_LT01_4_count   0.63842    0.09270   6.887 1.75e-11 ***
## category_code_LT01_5_count   0.90188    0.06089  14.811  < 2e-16 ***
## category_code_LT01_6_count   0.29990    0.15105   1.985   0.0477 *  
## category_code_LT01_9_count   0.33876    0.22030   1.538   0.1248    
## category_code_LT01_12_count -0.02098    0.20235  -0.104   0.9175    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6451, Adjusted R-squared:  0.6408 
## F-statistic: 148.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 0.640890810178982 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9553 -0.7417  0.0897  0.9293  3.4990 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94619    0.08534 116.553  < 2e-16 ***
## category_code_LT01_2_count   0.48517    0.09030   5.373 1.20e-07 ***
## category_code_LT01_4_count   0.63346    0.09301   6.811 2.85e-11 ***
## category_code_LT01_5_count   0.90055    0.06071  14.834  < 2e-16 ***
## category_code_LT01_6_count   0.29957    0.15032   1.993   0.0468 *  
## category_code_LT01_9_count   0.34486    0.22071   1.562   0.1188    
## category_code_LT01_13_count  0.10302    0.23780   0.433   0.6651    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6452, Adjusted R-squared:  0.6409 
## F-statistic: 148.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 0.640792757132589 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9558 -0.7395  0.0872  0.9264  3.4987 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94719    0.08543 116.442  < 2e-16 ***
## category_code_LT01_2_count   0.48612    0.09035   5.380 1.15e-07 ***
## category_code_LT01_4_count   0.63445    0.09360   6.779 3.49e-11 ***
## category_code_LT01_5_count   0.89986    0.06103  14.744  < 2e-16 ***
## category_code_LT01_6_count   0.30205    0.15115   1.998   0.0462 *  
## category_code_LT01_9_count   0.33535    0.22079   1.519   0.1294    
## category_code_LT01_14_count  0.07452    0.32191   0.231   0.8170    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6451, Adjusted R-squared:  0.6408 
## F-statistic: 148.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 0.640753593471723 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9560 -0.7401  0.0880  0.9225  3.4980 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.946339   0.085354 116.531  < 2e-16 ***
## category_code_LT01_2_count   0.487564   0.090304   5.399 1.04e-07 ***
## category_code_LT01_4_count   0.637830   0.092785   6.874 1.90e-11 ***
## category_code_LT01_5_count   0.901354   0.060701  14.849  < 2e-16 ***
## category_code_LT01_6_count   0.298405   0.150449   1.983   0.0479 *  
## category_code_LT01_9_count   0.338726   0.220382   1.537   0.1249    
## category_code_LT01_15_count -0.005588   0.732022  -0.008   0.9939    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6451, Adjusted R-squared:  0.6408 
## F-statistic: 148.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 0.640941978977171 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9557 -0.7370  0.0857  0.9326  3.4987 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94666    0.08533 116.565  < 2e-16 ***
## category_code_LT01_2_count   0.48140    0.09093   5.294 1.81e-07 ***
## category_code_LT01_4_count   0.63859    0.09249   6.905 1.56e-11 ***
## category_code_LT01_5_count   0.90042    0.06070  14.833  < 2e-16 ***
## category_code_LT01_6_count   0.30555    0.15095   2.024   0.0435 *  
## category_code_LT01_9_count   0.33488    0.22038   1.520   0.1293    
## category_code_LT01_16_count  0.58196    1.14647   0.508   0.6120    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6453, Adjusted R-squared:  0.6409 
## F-statistic: 148.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 0.64182960510133 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9547 -0.7318  0.0395  0.8619  3.4204 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94227    0.08835 112.537  < 2e-16 ***
## category_code_LT01_2_count   0.43648    0.09609   4.542 7.01e-06 ***
## category_code_LT01_4_count   0.58602    0.09776   5.995 3.95e-09 ***
## category_code_LT01_5_count   0.90535    0.06046  14.974  < 2e-16 ***
## category_code_LT01_6_count   0.26313    0.15252   1.725   0.0851 .  
## category_code_LT01_10_count  0.07029    0.11061   0.635   0.5254    
## category_code_LT01_11_count  0.21554    0.11677   1.846   0.0655 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6462, Adjusted R-squared:  0.6418 
## F-statistic: 149.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 0.639354503519139 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9490 -0.7373  0.0884  0.8833  3.4211 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93421    0.08855 112.193  < 2e-16 ***
## category_code_LT01_2_count   0.50235    0.09047   5.553 4.61e-08 ***
## category_code_LT01_4_count   0.64693    0.09268   6.980 9.62e-12 ***
## category_code_LT01_5_count   0.90870    0.06086  14.931  < 2e-16 ***
## category_code_LT01_6_count   0.29462    0.15287   1.927   0.0545 .  
## category_code_LT01_10_count  0.07362    0.11100   0.663   0.5075    
## category_code_LT01_12_count -0.02414    0.20279  -0.119   0.9053    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6394 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 0.639416508971582 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9484 -0.7240  0.0839  0.8838  3.4236 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93441    0.08854 112.205  < 2e-16 ***
## category_code_LT01_2_count   0.49963    0.08991   5.557 4.51e-08 ***
## category_code_LT01_4_count   0.64325    0.09295   6.921 1.41e-11 ***
## category_code_LT01_5_count   0.90760    0.06067  14.960  < 2e-16 ***
## category_code_LT01_6_count   0.29412    0.15223   1.932   0.0539 .  
## category_code_LT01_10_count  0.07228    0.11102   0.651   0.5153    
## category_code_LT01_13_count  0.07471    0.23791   0.314   0.7536    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6438, Adjusted R-squared:  0.6394 
## F-statistic: 147.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 0.639369610952736 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9494 -0.7255  0.0927  0.8933  3.4272 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93596    0.08901 111.633  < 2e-16 ***
## category_code_LT01_2_count   0.50001    0.08998   5.557 4.51e-08 ***
## category_code_LT01_4_count   0.64353    0.09358   6.877 1.87e-11 ***
## category_code_LT01_5_count   0.90681    0.06105  14.853  < 2e-16 ***
## category_code_LT01_6_count   0.29688    0.15367   1.932   0.0539 .  
## category_code_LT01_10_count  0.06845    0.11402   0.600   0.5486    
## category_code_LT01_14_count  0.06163    0.33066   0.186   0.8522    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6394 
## F-statistic: 147.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 0.639350880841648 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9483 -0.7336  0.0883  0.8870  3.4216 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93405    0.08857 112.155  < 2e-16 ***
## category_code_LT01_2_count   0.50148    0.08992   5.577 4.05e-08 ***
## category_code_LT01_4_count   0.64686    0.09274   6.975 9.92e-12 ***
## category_code_LT01_5_count   0.90798    0.06067  14.967  < 2e-16 ***
## category_code_LT01_6_count   0.29333    0.15226   1.927   0.0546 .  
## category_code_LT01_10_count  0.07410    0.11127   0.666   0.5058    
## category_code_LT01_15_count -0.07067    0.73511  -0.096   0.9235    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6394 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 0.639546755813342 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9488 -0.7471  0.0846  0.8956  3.4257 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93520    0.08854 112.213  < 2e-16 ***
## category_code_LT01_2_count   0.49466    0.09060   5.460 7.59e-08 ***
## category_code_LT01_4_count   0.64702    0.09247   6.997 8.60e-12 ***
## category_code_LT01_5_count   0.90704    0.06067  14.950  < 2e-16 ***
## category_code_LT01_6_count   0.30089    0.15291   1.968   0.0497 *  
## category_code_LT01_10_count  0.07023    0.11110   0.632   0.5276    
## category_code_LT01_16_count  0.60403    1.14962   0.525   0.5995    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6439, Adjusted R-squared:  0.6395 
## F-statistic:   148 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 0.641749265372548 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9716 -0.7470  0.0305  0.8489  3.4797 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95744    0.08531 116.723  < 2e-16 ***
## category_code_LT01_2_count   0.44180    0.09598   4.603 5.31e-06 ***
## category_code_LT01_4_count   0.58747    0.09772   6.012 3.58e-09 ***
## category_code_LT01_5_count   0.90786    0.06066  14.967  < 2e-16 ***
## category_code_LT01_6_count   0.28354    0.15131   1.874   0.0615 .  
## category_code_LT01_11_count  0.23146    0.11993   1.930   0.0542 .  
## category_code_LT01_12_count -0.11245    0.20753  -0.542   0.5882    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6461, Adjusted R-squared:  0.6417 
## F-statistic: 149.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 0.641580066046346 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9689 -0.7447  0.0613  0.8469  3.4836 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95680    0.08532 116.694  < 2e-16 ***
## category_code_LT01_2_count   0.43937    0.09600   4.577 6.00e-06 ***
## category_code_LT01_4_count   0.58618    0.09806   5.978 4.35e-09 ***
## category_code_LT01_5_count   0.90489    0.06050  14.956  < 2e-16 ***
## category_code_LT01_6_count   0.27835    0.15097   1.844   0.0658 .  
## category_code_LT01_11_count  0.21529    0.11692   1.841   0.0662 .  
## category_code_LT01_13_count  0.05895    0.23735   0.248   0.8040    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6459, Adjusted R-squared:  0.6416 
## F-statistic: 149.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 0.641600876206389 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9689 -0.7397  0.0682  0.8544  3.4843 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95794    0.08539 116.617  < 2e-16 ***
## category_code_LT01_2_count   0.43827    0.09615   4.558 6.52e-06 ***
## category_code_LT01_4_count   0.58390    0.09875   5.913 6.31e-09 ***
## category_code_LT01_5_count   0.90325    0.06085  14.843  < 2e-16 ***
## category_code_LT01_6_count   0.28211    0.15174   1.859   0.0636 .  
## category_code_LT01_11_count  0.21601    0.11681   1.849   0.0650 .  
## category_code_LT01_14_count  0.09637    0.32089   0.300   0.7641    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6459, Adjusted R-squared:  0.6416 
## F-statistic: 149.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 0.641545916674529 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9691 -0.7448  0.0483  0.8518  3.4833 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95685    0.08533 116.689  < 2e-16 ***
## category_code_LT01_2_count   0.44056    0.09603   4.588 5.69e-06 ***
## category_code_LT01_4_count   0.58887    0.09791   6.014 3.53e-09 ***
## category_code_LT01_5_count   0.90511    0.06050  14.960  < 2e-16 ***
## category_code_LT01_6_count   0.27803    0.15102   1.841   0.0662 .  
## category_code_LT01_11_count  0.21721    0.11689   1.858   0.0637 .  
## category_code_LT01_15_count -0.08930    0.73154  -0.122   0.9029    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6459, Adjusted R-squared:  0.6415 
## F-statistic: 149.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 0.641759354337173 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9688 -0.7433  0.0600  0.8531  3.4840 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95720    0.08530 116.727  < 2e-16 ***
## category_code_LT01_2_count   0.43330    0.09672   4.480 9.29e-06 ***
## category_code_LT01_4_count   0.58898    0.09772   6.027 3.28e-09 ***
## category_code_LT01_5_count   0.90416    0.06050  14.945  < 2e-16 ***
## category_code_LT01_6_count   0.28513    0.15153   1.882   0.0605 .  
## category_code_LT01_11_count  0.21640    0.11677   1.853   0.0644 .  
## category_code_LT01_16_count  0.63459    1.14448   0.554   0.5795    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6461, Adjusted R-squared:  0.6418 
## F-statistic: 149.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 0.639114580299692 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9637 -0.7384  0.0797  0.8821  3.4875 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94942    0.08552 116.338  < 2e-16 ***
## category_code_LT01_2_count   0.50486    0.09041   5.584 3.89e-08 ***
## category_code_LT01_4_count   0.64625    0.09311   6.941 1.24e-11 ***
## category_code_LT01_5_count   0.90806    0.06090  14.912  < 2e-16 ***
## category_code_LT01_6_count   0.31067    0.15131   2.053   0.0406 *  
## category_code_LT01_12_count -0.02287    0.20287  -0.113   0.9103    
## category_code_LT01_13_count  0.08003    0.23798   0.336   0.7368    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6391 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 0.639117613155878 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9638 -0.7391  0.0860  0.8876  3.4881 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95071    0.08560 116.253  < 2e-16 ***
## category_code_LT01_2_count   0.50430    0.09050   5.573 4.14e-08 ***
## category_code_LT01_4_count   0.64448    0.09375   6.875 1.89e-11 ***
## category_code_LT01_5_count   0.90637    0.06121  14.807  < 2e-16 ***
## category_code_LT01_6_count   0.31521    0.15219   2.071   0.0389 *  
## category_code_LT01_12_count -0.02673    0.20346  -0.131   0.8955    
## category_code_LT01_14_count  0.11058    0.32297   0.342   0.7322    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6391 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 0.639033366522032 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9641 -0.7386  0.0846  0.8934  3.4870 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94947    0.08553 116.322  < 2e-16 ***
## category_code_LT01_2_count   0.50661    0.09046   5.600 3.57e-08 ***
## category_code_LT01_4_count   0.64977    0.09294   6.991 8.93e-12 ***
## category_code_LT01_5_count   0.90850    0.06090  14.919  < 2e-16 ***
## category_code_LT01_6_count   0.30981    0.15143   2.046   0.0413 *  
## category_code_LT01_12_count -0.02145    0.20291  -0.106   0.9158    
## category_code_LT01_15_count -0.03743    0.73379  -0.051   0.9593    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6434, Adjusted R-squared:  0.639 
## F-statistic: 147.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 0.639260809688835 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9637 -0.7394  0.0782  0.9012  3.4878 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94980    0.08551 116.364  < 2e-16 ***
## category_code_LT01_2_count   0.49933    0.09115   5.478 6.87e-08 ***
## category_code_LT01_4_count   0.65013    0.09263   7.019 7.49e-12 ***
## category_code_LT01_5_count   0.90741    0.06090  14.900  < 2e-16 ***
## category_code_LT01_6_count   0.31723    0.15187   2.089   0.0372 *  
## category_code_LT01_12_count -0.02034    0.20277  -0.100   0.9201    
## category_code_LT01_16_count  0.64169    1.14849   0.559   0.5766    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 0.63918770988089 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9629 -0.7386  0.0814  0.8848  3.4894 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95060    0.08559 116.264  < 2e-16 ***
## category_code_LT01_2_count   0.50132    0.09000   5.570 4.19e-08 ***
## category_code_LT01_4_count   0.64059    0.09409   6.808 2.89e-11 ***
## category_code_LT01_5_count   0.90523    0.06106  14.824  < 2e-16 ***
## category_code_LT01_6_count   0.31419    0.15135   2.076   0.0384 *  
## category_code_LT01_13_count  0.07984    0.23788   0.336   0.7373    
## category_code_LT01_14_count  0.10784    0.32192   0.335   0.7378    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6392 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 0.639105764131549 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9633 -0.7382  0.0801  0.8849  3.4882 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94940    0.08553 116.333  < 2e-16 ***
## category_code_LT01_2_count   0.50377    0.08990   5.604 3.50e-08 ***
## category_code_LT01_4_count   0.64578    0.09324   6.926 1.37e-11 ***
## category_code_LT01_5_count   0.90747    0.06071  14.949  < 2e-16 ***
## category_code_LT01_6_count   0.30914    0.15068   2.052   0.0407 *  
## category_code_LT01_13_count  0.07895    0.23840   0.331   0.7406    
## category_code_LT01_15_count -0.01961    0.73498  -0.027   0.9787    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6391 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 0.639347139865027 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9628 -0.7393  0.0707  0.8840  3.4891 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94973    0.08550 116.376  < 2e-16 ***
## category_code_LT01_2_count   0.49635    0.09061   5.478 6.88e-08 ***
## category_code_LT01_4_count   0.64613    0.09289   6.956 1.13e-11 ***
## category_code_LT01_5_count   0.90631    0.06071  14.929  < 2e-16 ***
## category_code_LT01_6_count   0.31709    0.15118   2.097   0.0365 *  
## category_code_LT01_13_count  0.08503    0.23803   0.357   0.7211    
## category_code_LT01_16_count  0.65955    1.14930   0.574   0.5663    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 0.639106931005163 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9633 -0.7388  0.0872  0.8909  3.4889 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95064    0.08560 116.249  < 2e-16 ***
## category_code_LT01_2_count   0.50317    0.09001   5.590 3.77e-08 ***
## category_code_LT01_4_count   0.64418    0.09387   6.862 2.05e-11 ***
## category_code_LT01_5_count   0.90571    0.06106  14.832  < 2e-16 ***
## category_code_LT01_6_count   0.31341    0.15146   2.069    0.039 *  
## category_code_LT01_14_count  0.10740    0.32197   0.334    0.739    
## category_code_LT01_15_count -0.03832    0.73350  -0.052    0.958    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6391 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 0.639354064440306 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9629 -0.7407  0.0800  0.8982  3.4899 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95112    0.08557 116.292  < 2e-16 ***
## category_code_LT01_2_count   0.49537    0.09078   5.457  7.7e-08 ***
## category_code_LT01_4_count   0.64404    0.09358   6.882  1.8e-11 ***
## category_code_LT01_5_count   0.90435    0.06108  14.806  < 2e-16 ***
## category_code_LT01_6_count   0.32183    0.15203   2.117   0.0348 *  
## category_code_LT01_14_count  0.11939    0.32252   0.370   0.7114    
## category_code_LT01_16_count  0.67019    1.15073   0.582   0.5606    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6394 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 0.639254102513377 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9633 -0.7393  0.0785  0.9031  3.4885 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94978    0.08551 116.359  < 2e-16 ***
## category_code_LT01_2_count   0.49838    0.09062   5.499 6.14e-08 ***
## category_code_LT01_4_count   0.64972    0.09270   7.009 7.96e-12 ***
## category_code_LT01_5_count   0.90687    0.06071  14.939  < 2e-16 ***
## category_code_LT01_6_count   0.31591    0.15126   2.089   0.0373 *  
## category_code_LT01_15_count -0.02239    0.73366  -0.031   0.9757    
## category_code_LT01_16_count  0.64143    1.14904   0.558   0.5769    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 0.642729615848836 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9759 -0.7300  0.0480  0.8911  3.4737 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.95895    0.08505 117.093  < 2e-16 ***
## category_code_LT01_2_count  0.49931    0.08824   5.659 2.60e-08 ***
## category_code_LT01_4_count  0.61802    0.09320   6.631 8.79e-11 ***
## category_code_LT01_5_count  0.91194    0.06093  14.967  < 2e-16 ***
## category_code_LT01_7_count  0.38348    0.15138   2.533   0.0116 *  
## category_code_LT01_8_count -0.15617    0.26671  -0.586   0.5585    
## category_code_LT01_9_count  0.30998    0.22056   1.405   0.1605    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.647,  Adjusted R-squared:  0.6427 
## F-statistic:   150 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 0.641737563605503 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9644 -0.7171  0.0288  0.8650  3.3889 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94375    0.08831 112.603  < 2e-16 ***
## category_code_LT01_2_count   0.50852    0.08805   5.775 1.36e-08 ***
## category_code_LT01_4_count   0.62221    0.09328   6.670 6.89e-11 ***
## category_code_LT01_5_count   0.91727    0.06088  15.066  < 2e-16 ***
## category_code_LT01_7_count   0.39422    0.15136   2.605  0.00948 ** 
## category_code_LT01_8_count  -0.14864    0.26701  -0.557  0.57798    
## category_code_LT01_10_count  0.08569    0.10969   0.781  0.43509    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6461, Adjusted R-squared:  0.6417 
## F-statistic: 149.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 0.642938673127944 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9861 -0.7262  0.0119  0.8620  3.4623 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96707    0.08506 117.173  < 2e-16 ***
## category_code_LT01_2_count   0.46215    0.09431   4.900 1.30e-06 ***
## category_code_LT01_4_count   0.58085    0.09773   5.944 5.29e-09 ***
## category_code_LT01_5_count   0.91495    0.06081  15.047  < 2e-16 ***
## category_code_LT01_7_count   0.35089    0.15461   2.270   0.0237 *  
## category_code_LT01_8_count  -0.13310    0.26660  -0.499   0.6178    
## category_code_LT01_11_count  0.17890    0.11890   1.505   0.1331    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6472, Adjusted R-squared:  0.6429 
## F-statistic: 150.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 0.64130406297667 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9825 -0.7092  0.0520  0.8606  3.4652 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96201    0.08519 116.934  < 2e-16 ***
## category_code_LT01_2_count   0.51347    0.08867   5.791 1.25e-08 ***
## category_code_LT01_4_count   0.62502    0.09356   6.681 6.47e-11 ***
## category_code_LT01_5_count   0.91693    0.06115  14.996  < 2e-16 ***
## category_code_LT01_7_count   0.40290    0.15105   2.667   0.0079 ** 
## category_code_LT01_8_count  -0.14547    0.26730  -0.544   0.5865    
## category_code_LT01_12_count  0.02553    0.20136   0.127   0.8992    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6456, Adjusted R-squared:  0.6413 
## F-statistic: 149.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 0.641293739629599 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9830 -0.7145  0.0521  0.8579  3.4643 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96208    0.08519 116.934  < 2e-16 ***
## category_code_LT01_2_count   0.51526    0.08774   5.873 7.91e-09 ***
## category_code_LT01_4_count   0.62633    0.09344   6.703 5.61e-11 ***
## category_code_LT01_5_count   0.91767    0.06094  15.058  < 2e-16 ***
## category_code_LT01_7_count   0.40359    0.15208   2.654  0.00822 ** 
## category_code_LT01_8_count  -0.14490    0.26762  -0.541  0.58845    
## category_code_LT01_13_count -0.01054    0.23914  -0.044  0.96485    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6456, Adjusted R-squared:  0.6413 
## F-statistic: 149.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 0.641293472832809 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9830 -0.7150  0.0494  0.8552  3.4643 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96190    0.08529 116.806  < 2e-16 ***
## category_code_LT01_2_count   0.51529    0.08778   5.870 8.02e-09 ***
## category_code_LT01_4_count   0.62649    0.09388   6.673 6.78e-11 ***
## category_code_LT01_5_count   0.91782    0.06119  14.999  < 2e-16 ***
## category_code_LT01_7_count   0.40319    0.15136   2.664  0.00798 ** 
## category_code_LT01_8_count  -0.14404    0.26713  -0.539  0.59000    
## category_code_LT01_14_count -0.01271    0.31995  -0.040  0.96832    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6456, Adjusted R-squared:  0.6413 
## F-statistic: 149.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 0.641305372927983 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9831 -0.7112  0.0380  0.8571  3.4642 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96213    0.08519 116.935  < 2e-16 ***
## category_code_LT01_2_count   0.51430    0.08792   5.850 8.99e-09 ***
## category_code_LT01_4_count   0.62488    0.09361   6.675 6.69e-11 ***
## category_code_LT01_5_count   0.91773    0.06093  15.063  < 2e-16 ***
## category_code_LT01_7_count   0.40353    0.15115   2.670  0.00784 ** 
## category_code_LT01_8_count  -0.14463    0.26713  -0.541  0.58845    
## category_code_LT01_15_count  0.09773    0.73112   0.134  0.89372    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6456, Adjusted R-squared:  0.6413 
## F-statistic: 149.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 0.641429583026096 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9832 -0.7083  0.0414  0.8596  3.4644 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96254    0.08518 116.952  < 2e-16 ***
## category_code_LT01_2_count   0.51052    0.08832   5.780 1.33e-08 ***
## category_code_LT01_4_count   0.62729    0.09324   6.728 4.80e-11 ***
## category_code_LT01_5_count   0.91717    0.06092  15.056  < 2e-16 ***
## category_code_LT01_7_count   0.40382    0.15104   2.674  0.00776 ** 
## category_code_LT01_8_count  -0.15015    0.26742  -0.561  0.57473    
## category_code_LT01_16_count  0.49498    1.14171   0.434  0.66481    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6458, Adjusted R-squared:  0.6414 
## F-statistic: 149.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 0.64275993347013 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9562 -0.7100  0.0214  0.8958  3.4206 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94291    0.08815 112.790  < 2e-16 ***
## category_code_LT01_2_count   0.49551    0.08853   5.597 3.62e-08 ***
## category_code_LT01_4_count   0.61462    0.09328   6.589 1.15e-10 ***
## category_code_LT01_5_count   0.90661    0.06027  15.043  < 2e-16 ***
## category_code_LT01_7_count   0.37485    0.15161   2.473   0.0138 *  
## category_code_LT01_9_count   0.29056    0.22181   1.310   0.1908    
## category_code_LT01_10_count  0.06833    0.11019   0.620   0.5355    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6471, Adjusted R-squared:  0.6428 
## F-statistic:   150 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 0.644061793352298 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9745 -0.7213  0.0196  0.8987  3.4781 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96252    0.08492 117.313  < 2e-16 ***
## category_code_LT01_2_count   0.44857    0.09470   4.737 2.85e-06 ***
## category_code_LT01_4_count   0.57332    0.09766   5.870 8.01e-09 ***
## category_code_LT01_5_count   0.90468    0.06017  15.035  < 2e-16 ***
## category_code_LT01_7_count   0.33078    0.15478   2.137   0.0331 *  
## category_code_LT01_9_count   0.29530    0.22015   1.341   0.1804    
## category_code_LT01_11_count  0.17538    0.11873   1.477   0.1403    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.344 on 491 degrees of freedom
## Multiple R-squared:  0.6484, Adjusted R-squared:  0.6441 
## F-statistic: 150.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 0.642487582225121 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9703 -0.7060  0.0351  0.8965  3.4817 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95734    0.08504 117.090  < 2e-16 ***
## category_code_LT01_2_count   0.49868    0.08922   5.589 3.78e-08 ***
## category_code_LT01_4_count   0.61647    0.09357   6.588 1.15e-10 ***
## category_code_LT01_5_count   0.90613    0.06055  14.966  < 2e-16 ***
## category_code_LT01_7_count   0.38086    0.15136   2.516   0.0122 *  
## category_code_LT01_9_count   0.30576    0.22052   1.387   0.1662    
## category_code_LT01_12_count  0.02031    0.20088   0.101   0.9195    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6468, Adjusted R-squared:  0.6425 
## F-statistic: 149.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 0.64248665728545 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9706 -0.7109  0.0275  0.8948  3.4812 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95735    0.08504 117.091  < 2e-16 ***
## category_code_LT01_2_count   0.49965    0.08834   5.656 2.63e-08 ***
## category_code_LT01_4_count   0.61664    0.09347   6.597 1.09e-10 ***
## category_code_LT01_5_count   0.90656    0.06031  15.033  < 2e-16 ***
## category_code_LT01_7_count   0.37907    0.15247   2.486   0.0132 *  
## category_code_LT01_9_count   0.30743    0.22115   1.390   0.1651    
## category_code_LT01_13_count  0.02260    0.23897   0.095   0.9247    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6468, Adjusted R-squared:  0.6425 
## F-statistic: 149.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 0.642491624960179 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9707 -0.7015  0.0328  0.8939  3.4808 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95688    0.08513 116.954  < 2e-16 ***
## category_code_LT01_2_count   0.50040    0.08832   5.666 2.50e-08 ***
## category_code_LT01_4_count   0.61866    0.09386   6.592 1.13e-10 ***
## category_code_LT01_5_count   0.90740    0.06055  14.986  < 2e-16 ***
## category_code_LT01_7_count   0.38192    0.15162   2.519   0.0121 *  
## category_code_LT01_9_count   0.30742    0.22087   1.392   0.1646    
## category_code_LT01_14_count -0.04017    0.31990  -0.126   0.9001    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6468, Adjusted R-squared:  0.6425 
## F-statistic: 149.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 0.642498071985263 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9709 -0.7084  0.0345  0.8959  3.4808 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95745    0.08504 117.093  < 2e-16 ***
## category_code_LT01_2_count   0.49899    0.08850   5.638 2.90e-08 ***
## category_code_LT01_4_count   0.61591    0.09364   6.578 1.23e-10 ***
## category_code_LT01_5_count   0.90682    0.06029  15.040  < 2e-16 ***
## category_code_LT01_7_count   0.38159    0.15144   2.520   0.0121 *  
## category_code_LT01_9_count   0.30660    0.22057   1.390   0.1651    
## category_code_LT01_15_count  0.11456    0.73001   0.157   0.8754    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6468, Adjusted R-squared:  0.6425 
## F-statistic: 149.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 0.642575202129186 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9708 -0.7021  0.0361  0.9004  3.4812 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95776    0.08503 117.102  < 2e-16 ***
## category_code_LT01_2_count   0.49631    0.08884   5.586 3.85e-08 ***
## category_code_LT01_4_count   0.61837    0.09326   6.631 8.82e-11 ***
## category_code_LT01_5_count   0.90622    0.06030  15.029  < 2e-16 ***
## category_code_LT01_7_count   0.38171    0.15136   2.522    0.012 *  
## category_code_LT01_9_count   0.30328    0.22061   1.375    0.170    
## category_code_LT01_16_count  0.41158    1.13896   0.361    0.718    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.347 on 491 degrees of freedom
## Multiple R-squared:  0.6469, Adjusted R-squared:  0.6426 
## F-statistic: 149.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 0.643164287218593 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9638 -0.7220  0.0094  0.8883  3.3967 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94817    0.08818 112.812  < 2e-16 ***
## category_code_LT01_2_count   0.45616    0.09462   4.821 1.91e-06 ***
## category_code_LT01_4_count   0.57637    0.09777   5.895 6.97e-09 ***
## category_code_LT01_5_count   0.90995    0.06010  15.141  < 2e-16 ***
## category_code_LT01_7_count   0.34001    0.15481   2.196   0.0285 *  
## category_code_LT01_10_count  0.08190    0.10946   0.748   0.4547    
## category_code_LT01_11_count  0.17921    0.11883   1.508   0.1322    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.345 on 491 degrees of freedom
## Multiple R-squared:  0.6475, Adjusted R-squared:  0.6432 
## F-statistic: 150.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 0.64151585881455 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9594 -0.7155  0.0473  0.8682  3.3980 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94253    0.08831 112.589  < 2e-16 ***
## category_code_LT01_2_count   0.50808    0.08899   5.709 1.97e-08 ***
## category_code_LT01_4_count   0.62086    0.09364   6.630 8.85e-11 ***
## category_code_LT01_5_count   0.91177    0.06048  15.076  < 2e-16 ***
## category_code_LT01_7_count   0.39163    0.15133   2.588  0.00994 ** 
## category_code_LT01_10_count  0.08406    0.10977   0.766  0.44418    
## category_code_LT01_12_count  0.01568    0.20129   0.078  0.93793    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6458, Adjusted R-squared:  0.6415 
## F-statistic: 149.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 0.641511877768447 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9597 -0.7168  0.0434  0.8657  3.3971 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94250    0.08831 112.589  < 2e-16 ***
## category_code_LT01_2_count   0.50914    0.08811   5.778 1.34e-08 ***
## category_code_LT01_4_count   0.62163    0.09351   6.647 7.95e-11 ***
## category_code_LT01_5_count   0.91223    0.06023  15.146  < 2e-16 ***
## category_code_LT01_7_count   0.39199    0.15230   2.574   0.0103 *  
## category_code_LT01_10_count  0.08443    0.10972   0.769   0.4420    
## category_code_LT01_13_count -0.00593    0.23865  -0.025   0.9802    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6458, Adjusted R-squared:  0.6415 
## F-statistic: 149.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 0.641543709708714 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9586 -0.7156  0.0441  0.8662  3.3924 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94062    0.08876 111.996  < 2e-16 ***
## category_code_LT01_2_count   0.50952    0.08809   5.784 1.30e-08 ***
## category_code_LT01_4_count   0.62367    0.09388   6.643 8.16e-11 ***
## category_code_LT01_5_count   0.91344    0.06050  15.098  < 2e-16 ***
## category_code_LT01_7_count   0.39314    0.15151   2.595  0.00975 ** 
## category_code_LT01_10_count  0.08925    0.11212   0.796  0.42639    
## category_code_LT01_14_count -0.06874    0.32688  -0.210  0.83353    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6459, Adjusted R-squared:  0.6415 
## F-statistic: 149.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 0.641514537904015 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9599 -0.7161  0.0429  0.8667  3.3976 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94266    0.08834 112.552  < 2e-16 ***
## category_code_LT01_2_count   0.50871    0.08825   5.765 1.45e-08 ***
## category_code_LT01_4_count   0.62093    0.09367   6.629 8.94e-11 ***
## category_code_LT01_5_count   0.91227    0.06023  15.147  < 2e-16 ***
## category_code_LT01_7_count   0.39197    0.15146   2.588  0.00994 ** 
## category_code_LT01_10_count  0.08380    0.11005   0.761  0.44675    
## category_code_LT01_15_count  0.04786    0.73320   0.065  0.94798    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6458, Adjusted R-squared:  0.6415 
## F-statistic: 149.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 0.641614162021911 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9600 -0.7153  0.0393  0.8757  3.3988 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94322    0.08832 112.588  < 2e-16 ***
## category_code_LT01_2_count   0.50522    0.08866   5.699 2.08e-08 ***
## category_code_LT01_4_count   0.62260    0.09333   6.671 6.88e-11 ***
## category_code_LT01_5_count   0.91167    0.06023  15.137  < 2e-16 ***
## category_code_LT01_7_count   0.39250    0.15133   2.594  0.00978 ** 
## category_code_LT01_10_count  0.08275    0.10977   0.754  0.45130    
## category_code_LT01_16_count  0.42799    1.14079   0.375  0.70770    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.348 on 491 degrees of freedom
## Multiple R-squared:  0.6459, Adjusted R-squared:  0.6416 
## F-statistic: 149.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 0.64281076367113 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9830 -0.7330  0.0128  0.8639  3.4667 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96612    0.08505 117.182  < 2e-16 ***
## category_code_LT01_2_count   0.46333    0.09444   4.906 1.27e-06 ***
## category_code_LT01_4_count   0.57995    0.09772   5.935 5.57e-09 ***
## category_code_LT01_5_count   0.91185    0.06037  15.105  < 2e-16 ***
## category_code_LT01_7_count   0.34546    0.15479   2.232   0.0261 *  
## category_code_LT01_11_count  0.18860    0.12255   1.539   0.1244    
## category_code_LT01_12_count -0.05605    0.20699  -0.271   0.7867    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6471, Adjusted R-squared:  0.6428 
## F-statistic: 150.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 0.642758603081946 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9817 -0.7142  0.0239  0.8648  3.4686 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96576    0.08504 117.184  < 2e-16 ***
## category_code_LT01_2_count   0.46216    0.09436   4.898 1.32e-06 ***
## category_code_LT01_4_count   0.57995    0.09790   5.924 5.91e-09 ***
## category_code_LT01_5_count   0.91044    0.06014  15.139  < 2e-16 ***
## category_code_LT01_7_count   0.34859    0.15542   2.243   0.0254 *  
## category_code_LT01_11_count  0.18063    0.11891   1.519   0.1294    
## category_code_LT01_13_count -0.00958    0.23824  -0.040   0.9679    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6471, Adjusted R-squared:  0.6428 
## F-statistic:   150 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 0.642758338777765 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9817 -0.7144  0.0238  0.8649  3.4685 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96561    0.08513 117.057  < 2e-16 ***
## category_code_LT01_2_count   0.46222    0.09443   4.895 1.34e-06 ***
## category_code_LT01_4_count   0.58012    0.09839   5.896 6.94e-09 ***
## category_code_LT01_5_count   0.91060    0.06042  15.072  < 2e-16 ***
## category_code_LT01_7_count   0.34827    0.15485   2.249   0.0249 *  
## category_code_LT01_11_count  0.18051    0.11889   1.518   0.1296    
## category_code_LT01_14_count -0.01130    0.31928  -0.035   0.9718    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6471, Adjusted R-squared:  0.6428 
## F-statistic:   150 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 0.642759007882606 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9817 -0.7142  0.0178  0.8657  3.4686 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96576    0.08504 117.184  < 2e-16 ***
## category_code_LT01_2_count   0.46187    0.09444   4.891 1.36e-06 ***
## category_code_LT01_4_count   0.57939    0.09798   5.913 6.30e-09 ***
## category_code_LT01_5_count   0.91044    0.06014  15.139  < 2e-16 ***
## category_code_LT01_7_count   0.34825    0.15469   2.251   0.0248 *  
## category_code_LT01_11_count  0.18025    0.11905   1.514   0.1307    
## category_code_LT01_15_count  0.03406    0.73060   0.047   0.9628    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6471, Adjusted R-squared:  0.6428 
## F-statistic:   150 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 0.642880399548513 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9817 -0.7111  0.0302  0.8697  3.4689 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96615    0.08503 117.201  < 2e-16 ***
## category_code_LT01_2_count   0.45768    0.09493   4.821 1.90e-06 ***
## category_code_LT01_4_count   0.58082    0.09775   5.942 5.33e-09 ***
## category_code_LT01_5_count   0.90979    0.06014  15.128  < 2e-16 ***
## category_code_LT01_7_count   0.34872    0.15452   2.257   0.0245 *  
## category_code_LT01_11_count  0.18071    0.11887   1.520   0.1291    
## category_code_LT01_16_count  0.46789    1.13789   0.411   0.6811    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.346 on 491 degrees of freedom
## Multiple R-squared:  0.6472, Adjusted R-squared:  0.6429 
## F-statistic: 150.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 0.641087836014223 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9776 -0.7052  0.0643  0.8644  3.4720 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.960531   0.085175 116.941  < 2e-16 ***
## category_code_LT01_2_count   0.514221   0.088724   5.796 1.22e-08 ***
## category_code_LT01_4_count   0.624490   0.093786   6.659 7.42e-11 ***
## category_code_LT01_5_count   0.912097   0.060521  15.071  < 2e-16 ***
## category_code_LT01_7_count   0.400390   0.152005   2.634   0.0087 ** 
## category_code_LT01_12_count  0.021408   0.201325   0.106   0.9154    
## category_code_LT01_13_count -0.003144   0.238813  -0.013   0.9895    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6454, Adjusted R-squared:  0.6411 
## F-statistic:   149 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 0.641089852371237 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9776 -0.7050  0.0630  0.8619  3.4719 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96031    0.08527 116.813  < 2e-16 ***
## category_code_LT01_2_count   0.51435    0.08874   5.796 1.21e-08 ***
## category_code_LT01_4_count   0.62499    0.09419   6.635 8.57e-11 ***
## category_code_LT01_5_count   0.91238    0.06076  15.016  < 2e-16 ***
## category_code_LT01_7_count   0.40069    0.15132   2.648  0.00836 ** 
## category_code_LT01_12_count  0.02210    0.20175   0.110  0.91281    
## category_code_LT01_14_count -0.01737    0.32078  -0.054  0.95684    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6454, Adjusted R-squared:  0.6411 
## F-statistic:   149 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 0.641099897420372 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9777 -0.7047  0.0583  0.8652  3.4718 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96059    0.08517 116.943  < 2e-16 ***
## category_code_LT01_2_count   0.51334    0.08893   5.773 1.38e-08 ***
## category_code_LT01_4_count   0.62326    0.09400   6.630 8.85e-11 ***
## category_code_LT01_5_count   0.91218    0.06052  15.073  < 2e-16 ***
## category_code_LT01_7_count   0.40084    0.15110   2.653  0.00824 ** 
## category_code_LT01_12_count  0.02195    0.20132   0.109  0.91324    
## category_code_LT01_15_count  0.09445    0.73146   0.129  0.89731    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6454, Adjusted R-squared:  0.6411 
## F-statistic:   149 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 0.641208646378595 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9776 -0.7005  0.0608  0.8654  3.4723 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96092    0.08517 116.958  < 2e-16 ***
## category_code_LT01_2_count   0.50979    0.08933   5.707 1.99e-08 ***
## category_code_LT01_4_count   0.62549    0.09360   6.683 6.39e-11 ***
## category_code_LT01_5_count   0.91145    0.06052  15.060  < 2e-16 ***
## category_code_LT01_7_count   0.40100    0.15100   2.656  0.00817 ** 
## category_code_LT01_12_count  0.02270    0.20126   0.113  0.91026    
## category_code_LT01_16_count  0.46406    1.14070   0.407  0.68432    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6455, Adjusted R-squared:  0.6412 
## F-statistic:   149 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 0.64108117120007 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9781 -0.7058  0.0583  0.8591  3.4711 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.960399   0.085265 116.817  < 2e-16 ***
## category_code_LT01_2_count   0.515787   0.087849   5.871 7.97e-09 ***
## category_code_LT01_4_count   0.625870   0.094130   6.649 7.88e-11 ***
## category_code_LT01_5_count   0.912966   0.060549  15.078  < 2e-16 ***
## category_code_LT01_7_count   0.400756   0.152320   2.631  0.00878 ** 
## category_code_LT01_13_count -0.002681   0.238766  -0.011  0.99104    
## category_code_LT01_14_count -0.014977   0.320039  -0.047  0.96269    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6454, Adjusted R-squared:  0.6411 
## F-statistic:   149 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 0.641091216768004 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9782 -0.7027  0.0546  0.8618  3.4711 
## 
## Coefficients:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.9606391  0.0851748 116.943  < 2e-16 ***
## category_code_LT01_2_count   0.5147954  0.0879968   5.850 8.98e-09 ***
## category_code_LT01_4_count   0.6241859  0.0938911   6.648 7.93e-11 ***
## category_code_LT01_5_count   0.9127969  0.0602680  15.146  < 2e-16 ***
## category_code_LT01_7_count   0.4008273  0.1520596   2.636  0.00865 ** 
## category_code_LT01_13_count -0.0006909  0.2392054  -0.003  0.99770    
## category_code_LT01_15_count  0.0924816  0.7326739   0.126  0.89961    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6454, Adjusted R-squared:  0.6411 
## F-statistic:   149 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 0.641199370723139 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9781 -0.7003  0.0583  0.8606  3.4715 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.960972   0.085166 116.959  < 2e-16 ***
## category_code_LT01_2_count  0.511267   0.088401   5.784 1.30e-08 ***
## category_code_LT01_4_count  0.626375   0.093466   6.702 5.67e-11 ***
## category_code_LT01_5_count  0.912083   0.060272  15.133  < 2e-16 ***
## category_code_LT01_7_count  0.400865   0.151985   2.638  0.00862 ** 
## category_code_LT01_13_count 0.001117   0.238885   0.005  0.99627    
## category_code_LT01_16_count 0.462142   1.141385   0.405  0.68573    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6455, Adjusted R-squared:  0.6412 
## F-statistic:   149 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 0.641092893465892 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9782 -0.7032  0.0528  0.8598  3.4710 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96045    0.08526 116.818  < 2e-16 ***
## category_code_LT01_2_count   0.51497    0.08802   5.851 8.95e-09 ***
## category_code_LT01_4_count   0.62470    0.09430   6.625 9.15e-11 ***
## category_code_LT01_5_count   0.91308    0.06054  15.081  < 2e-16 ***
## category_code_LT01_7_count   0.40124    0.15141   2.650  0.00831 ** 
## category_code_LT01_14_count -0.01536    0.32003  -0.048  0.96175    
## category_code_LT01_15_count  0.09297    0.73131   0.127  0.89889    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6454, Adjusted R-squared:  0.6411 
## F-statistic:   149 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 0.641199805159087 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9781 -0.7006  0.0575  0.8597  3.4715 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.960873   0.085259 116.830  < 2e-16 ***
## category_code_LT01_2_count   0.511392   0.088452   5.782 1.32e-08 ***
## category_code_LT01_4_count   0.626681   0.093913   6.673 6.78e-11 ***
## category_code_LT01_5_count   0.912236   0.060554  15.065  < 2e-16 ***
## category_code_LT01_7_count   0.401182   0.151304   2.651  0.00827 ** 
## category_code_LT01_14_count -0.007955   0.320435  -0.025  0.98020    
## category_code_LT01_16_count  0.460406   1.142230   0.403  0.68707    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6455, Adjusted R-squared:  0.6412 
## F-statistic:   149 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 0.641213922405944 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9782 -0.6991  0.0451  0.8632  3.4713 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96104    0.08517 116.961  < 2e-16 ***
## category_code_LT01_2_count   0.51035    0.08859   5.761 1.48e-08 ***
## category_code_LT01_4_count   0.62519    0.09365   6.676 6.66e-11 ***
## category_code_LT01_5_count   0.91221    0.06027  15.137  < 2e-16 ***
## category_code_LT01_7_count   0.40170    0.15110   2.659   0.0081 ** 
## category_code_LT01_15_count  0.10330    0.73161   0.141   0.8878    
## category_code_LT01_16_count  0.46768    1.14126   0.410   0.6821    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6455, Adjusted R-squared:  0.6412 
## F-statistic:   149 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 0.638512580402494 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9594 -0.7325  0.0727  0.8735  3.3924 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93808    0.08867 112.079  < 2e-16 ***
## category_code_LT01_2_count   0.52196    0.08838   5.906 6.55e-09 ***
## category_code_LT01_4_count   0.67165    0.09104   7.377 6.93e-13 ***
## category_code_LT01_5_count   0.91819    0.06124  14.994  < 2e-16 ***
## category_code_LT01_8_count  -0.14002    0.26821  -0.522    0.602    
## category_code_LT01_9_count   0.34047    0.22245   1.531    0.127    
## category_code_LT01_10_count  0.08674    0.11064   0.784    0.433    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.354 on 491 degrees of freedom
## Multiple R-squared:  0.6429, Adjusted R-squared:  0.6385 
## F-statistic: 147.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 0.640909722805902 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9819 -0.7529  0.0811  0.8478  3.4669 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96339    0.08534 116.755  < 2e-16 ***
## category_code_LT01_2_count   0.45596    0.09506   4.797 2.14e-06 ***
## category_code_LT01_4_count   0.60851    0.09683   6.285 7.26e-10 ***
## category_code_LT01_5_count   0.91407    0.06107  14.967  < 2e-16 ***
## category_code_LT01_8_count  -0.12455    0.26733  -0.466    0.641    
## category_code_LT01_9_count   0.33785    0.22051   1.532    0.126    
## category_code_LT01_11_count  0.22975    0.11639   1.974    0.049 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6452, Adjusted R-squared:  0.6409 
## F-statistic: 148.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 0.638069228070832 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9773 -0.7538  0.0652  0.8675  3.4700 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95633    0.08560 116.313  < 2e-16 ***
## category_code_LT01_2_count   0.52678    0.08904   5.916 6.18e-09 ***
## category_code_LT01_4_count   0.67527    0.09127   7.399 5.99e-13 ***
## category_code_LT01_5_count   0.91771    0.06150  14.922  < 2e-16 ***
## category_code_LT01_8_count  -0.13697    0.26852  -0.510    0.610    
## category_code_LT01_9_count   0.36071    0.22107   1.632    0.103    
## category_code_LT01_12_count  0.02249    0.20226   0.111    0.912    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6424, Adjusted R-squared:  0.6381 
## F-statistic:   147 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 0.638159523908854 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9770 -0.7495  0.0613  0.8769  3.4704 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95622    0.08559 116.326  < 2e-16 ***
## category_code_LT01_2_count   0.52639    0.08820   5.968 4.60e-09 ***
## category_code_LT01_4_count   0.67257    0.09143   7.356 7.98e-13 ***
## category_code_LT01_5_count   0.91746    0.06131  14.964  < 2e-16 ***
## category_code_LT01_8_count  -0.13037    0.26870  -0.485   0.6278    
## category_code_LT01_9_count   0.36586    0.22148   1.652   0.0992 .  
## category_code_LT01_13_count  0.08779    0.23903   0.367   0.7136    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6425, Adjusted R-squared:  0.6382 
## F-statistic: 147.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 0.638060670510382 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9778 -0.7547  0.0619  0.8700  3.4694 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.956488   0.085701 116.177  < 2e-16 ***
## category_code_LT01_2_count   0.528128   0.088155   5.991 4.04e-09 ***
## category_code_LT01_4_count   0.675822   0.091743   7.366 7.46e-13 ***
## category_code_LT01_5_count   0.918141   0.061540  14.919  < 2e-16 ***
## category_code_LT01_8_count  -0.135933   0.268351  -0.507    0.613    
## category_code_LT01_9_count   0.360391   0.221496   1.627    0.104    
## category_code_LT01_14_count  0.008798   0.321362   0.027    0.978    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6424, Adjusted R-squared:  0.6381 
## F-statistic:   147 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 0.638064896815846 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9779 -0.7549  0.0614  0.8717  3.4692 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95641    0.08560 116.313  < 2e-16 ***
## category_code_LT01_2_count   0.52774    0.08828   5.978 4.35e-09 ***
## category_code_LT01_4_count   0.67551    0.09128   7.401 5.92e-13 ***
## category_code_LT01_5_count   0.91838    0.06128  14.986  < 2e-16 ***
## category_code_LT01_8_count  -0.13611    0.26835  -0.507    0.612    
## category_code_LT01_9_count   0.36121    0.22114   1.633    0.103    
## category_code_LT01_15_count  0.05911    0.73419   0.081    0.936    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6424, Adjusted R-squared:  0.6381 
## F-statistic:   147 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 0.638147071402774 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9780 -0.7532  0.0613  0.8698  3.4692 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95677    0.08560 116.321  < 2e-16 ***
## category_code_LT01_2_count   0.52475    0.08864   5.920 6.06e-09 ***
## category_code_LT01_4_count   0.67735    0.09097   7.446 4.36e-13 ***
## category_code_LT01_5_count   0.91801    0.06127  14.982  < 2e-16 ***
## category_code_LT01_8_count  -0.14046    0.26863  -0.523    0.601    
## category_code_LT01_9_count   0.35856    0.22114   1.621    0.106    
## category_code_LT01_16_count  0.39408    1.14728   0.343    0.731    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6425, Adjusted R-squared:  0.6381 
## F-statistic: 147.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 0.639795615982591 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9682 -0.7375  0.0786  0.8511  3.3690 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94565    0.08861 112.241  < 2e-16 ***
## category_code_LT01_2_count   0.46450    0.09499   4.890 1.37e-06 ***
## category_code_LT01_4_count   0.61273    0.09695   6.320 5.87e-10 ***
## category_code_LT01_5_count   0.91994    0.06103  15.075  < 2e-16 ***
## category_code_LT01_8_count  -0.11574    0.26765  -0.432   0.6656    
## category_code_LT01_10_count  0.09947    0.10975   0.906   0.3652    
## category_code_LT01_11_count  0.23582    0.11647   2.025   0.0434 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6441, Adjusted R-squared:  0.6398 
## F-statistic: 148.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 0.636792683714436 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9628 -0.7478  0.0611  0.8515  3.3653 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93722    0.08888 111.804  < 2e-16 ***
## category_code_LT01_2_count   0.53838    0.08878   6.064 2.65e-09 ***
## category_code_LT01_4_count   0.68196    0.09131   7.469 3.73e-13 ***
## category_code_LT01_5_count   0.92428    0.06146  15.038  < 2e-16 ***
## category_code_LT01_8_count  -0.12754    0.26890  -0.474    0.635    
## category_code_LT01_10_count  0.10614    0.11022   0.963    0.336    
## category_code_LT01_12_count  0.01624    0.20275   0.080    0.936    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 491 degrees of freedom
## Multiple R-squared:  0.6412, Adjusted R-squared:  0.6368 
## F-statistic: 146.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 0.636829465321033 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9628 -0.7475  0.0514  0.8500  3.3658 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93727    0.08888 111.811  < 2e-16 ***
## category_code_LT01_2_count   0.53847    0.08793   6.124 1.88e-09 ***
## category_code_LT01_4_count   0.68043    0.09142   7.443 4.45e-13 ***
## category_code_LT01_5_count   0.92423    0.06126  15.086  < 2e-16 ***
## category_code_LT01_8_count  -0.12303    0.26915  -0.457    0.648    
## category_code_LT01_10_count  0.10572    0.11019   0.959    0.338    
## category_code_LT01_13_count  0.05665    0.23909   0.237    0.813    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 491 degrees of freedom
## Multiple R-squared:  0.6412, Adjusted R-squared:  0.6368 
## F-statistic: 146.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 0.636792329587568 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9626 -0.7491  0.0574  0.8469  3.3627 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93648    0.08935 111.207  < 2e-16 ***
## category_code_LT01_2_count   0.53962    0.08789   6.140 1.71e-09 ***
## category_code_LT01_4_count   0.68348    0.09172   7.452 4.18e-13 ***
## category_code_LT01_5_count   0.92516    0.06152  15.037  < 2e-16 ***
## category_code_LT01_8_count  -0.12653    0.26872  -0.471    0.638    
## category_code_LT01_10_count  0.10828    0.11267   0.961    0.337    
## category_code_LT01_14_count -0.02533    0.32865  -0.077    0.939    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 491 degrees of freedom
## Multiple R-squared:  0.6412, Adjusted R-squared:  0.6368 
## F-statistic: 146.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 0.636788853916725 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9629 -0.7483  0.0589  0.8476  3.3643 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93711    0.08891 111.767  < 2e-16 ***
## category_code_LT01_2_count   0.53959    0.08800   6.132 1.79e-09 ***
## category_code_LT01_4_count   0.68285    0.09128   7.481 3.43e-13 ***
## category_code_LT01_5_count   0.92466    0.06125  15.097  < 2e-16 ***
## category_code_LT01_8_count  -0.12664    0.26873  -0.471    0.638    
## category_code_LT01_10_count  0.10675    0.11048   0.966    0.334    
## category_code_LT01_15_count -0.02597    0.73744  -0.035    0.972    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 491 degrees of freedom
## Multiple R-squared:  0.6412, Adjusted R-squared:  0.6368 
## F-statistic: 146.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 0.636880793638696 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9635 -0.7469  0.0564  0.8552  3.3658 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93789    0.08889 111.799  < 2e-16 ***
## category_code_LT01_2_count   0.53580    0.08842   6.059 2.72e-09 ***
## category_code_LT01_4_count   0.68383    0.09103   7.512 2.77e-13 ***
## category_code_LT01_5_count   0.92437    0.06123  15.096  < 2e-16 ***
## category_code_LT01_8_count  -0.13152    0.26902  -0.489    0.625    
## category_code_LT01_10_count  0.10500    0.11022   0.953    0.341    
## category_code_LT01_16_count  0.40735    1.14959   0.354    0.723    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 491 degrees of freedom
## Multiple R-squared:  0.6413, Adjusted R-squared:  0.6369 
## F-statistic: 146.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 0.639300669501201 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9916 -0.7565  0.0769  0.8536  3.4539 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96742    0.08550 116.572  < 2e-16 ***
## category_code_LT01_2_count   0.47362    0.09480   4.996 8.14e-07 ***
## category_code_LT01_4_count   0.61766    0.09685   6.377 4.17e-10 ***
## category_code_LT01_5_count   0.92231    0.06126  15.056  < 2e-16 ***
## category_code_LT01_8_count  -0.10531    0.26802  -0.393   0.6945    
## category_code_LT01_11_count  0.25003    0.11991   2.085   0.0376 *  
## category_code_LT01_12_count -0.07959    0.20785  -0.383   0.7019    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 0.639215853949845 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9895 -0.7509  0.0782  0.8395  3.4568 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96687    0.08551 116.563  < 2e-16 ***
## category_code_LT01_2_count   0.47148    0.09474   4.976 8.98e-07 ***
## category_code_LT01_4_count   0.61638    0.09717   6.343 5.12e-10 ***
## category_code_LT01_5_count   0.92012    0.06110  15.059  < 2e-16 ***
## category_code_LT01_8_count  -0.10714    0.26822  -0.399   0.6897    
## category_code_LT01_11_count  0.23825    0.11661   2.043   0.0416 *  
## category_code_LT01_13_count  0.04209    0.23843   0.177   0.8600    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:  0.6392 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 0.639202431215854 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9898 -0.7511  0.0800  0.8520  3.4567 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96740    0.08560 116.441  < 2e-16 ***
## category_code_LT01_2_count   0.47144    0.09481   4.973 9.15e-07 ***
## category_code_LT01_4_count   0.61633    0.09767   6.310 6.23e-10 ***
## category_code_LT01_5_count   0.91978    0.06136  14.990  < 2e-16 ***
## category_code_LT01_8_count  -0.11028    0.26782  -0.412   0.6807    
## category_code_LT01_11_count  0.23904    0.11651   2.052   0.0407 *  
## category_code_LT01_14_count  0.03636    0.32025   0.114   0.9096    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:  0.6392 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 0.639194867909142 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9898 -0.7516  0.0796  0.8507  3.4565 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96693    0.08551 116.561  < 2e-16 ***
## category_code_LT01_2_count   0.47215    0.09480   4.981 8.80e-07 ***
## category_code_LT01_4_count   0.61807    0.09708   6.367 4.44e-10 ***
## category_code_LT01_5_count   0.92039    0.06109  15.067  < 2e-16 ***
## category_code_LT01_8_count  -0.10965    0.26782  -0.409   0.6824    
## category_code_LT01_11_count  0.23940    0.11662   2.053   0.0406 *  
## category_code_LT01_15_count -0.03741    0.73352  -0.051   0.9593    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:  0.6392 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 0.639311940259673 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9900 -0.7513  0.0771  0.8509  3.4564 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96740    0.08550 116.576  < 2e-16 ***
## category_code_LT01_2_count   0.46764    0.09529   4.907 1.26e-06 ***
## category_code_LT01_4_count   0.61898    0.09690   6.388 3.91e-10 ***
## category_code_LT01_5_count   0.92007    0.06107  15.065  < 2e-16 ***
## category_code_LT01_8_count  -0.11532    0.26810  -0.430   0.6673    
## category_code_LT01_11_count  0.23939    0.11649   2.055   0.0404 *  
## category_code_LT01_16_count  0.46080    1.14496   0.402   0.6875    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6437, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 0.63615720976332 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9853 -0.7493  0.0434  0.8373  3.4594 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95976    0.08580 116.083  < 2e-16 ***
## category_code_LT01_2_count   0.54598    0.08849   6.170 1.43e-09 ***
## category_code_LT01_4_count   0.68573    0.09162   7.485 3.34e-13 ***
## category_code_LT01_5_count   0.92422    0.06154  15.018  < 2e-16 ***
## category_code_LT01_8_count  -0.11762    0.26952  -0.436    0.663    
## category_code_LT01_12_count  0.02187    0.20286   0.108    0.914    
## category_code_LT01_13_count  0.06243    0.23929   0.261    0.794    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6362 
## F-statistic: 145.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 0.636117464729457 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9857 -0.7499  0.0524  0.8356  3.4591 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96032    0.08590 115.953  < 2e-16 ***
## category_code_LT01_2_count   0.54656    0.08849   6.177 1.37e-09 ***
## category_code_LT01_4_count   0.68662    0.09199   7.464 3.86e-13 ***
## category_code_LT01_5_count   0.92403    0.06177  14.959  < 2e-16 ***
## category_code_LT01_8_count  -0.12213    0.26910  -0.454    0.650    
## category_code_LT01_12_count  0.02151    0.20328   0.106    0.916    
## category_code_LT01_14_count  0.03872    0.32236   0.120    0.904    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6361 
## F-statistic: 145.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 0.636108081411149 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9857 -0.7494  0.0491  0.8373  3.4588 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95985    0.08581 116.075  < 2e-16 ***
## category_code_LT01_2_count   0.54675    0.08862   6.169 1.43e-09 ***
## category_code_LT01_4_count   0.68775    0.09153   7.514 2.74e-13 ***
## category_code_LT01_5_count   0.92475    0.06153  15.030  < 2e-16 ***
## category_code_LT01_8_count  -0.12187    0.26910  -0.453    0.651    
## category_code_LT01_12_count  0.02338    0.20286   0.115    0.908    
## category_code_LT01_15_count  0.03094    0.73614   0.042    0.966    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6361 
## F-statistic: 145.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 0.636220550720815 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9858 -0.7498  0.0437  0.8370  3.4588 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96026    0.08580 116.090  < 2e-16 ***
## category_code_LT01_2_count   0.54278    0.08905   6.095 2.21e-09 ***
## category_code_LT01_4_count   0.68931    0.09121   7.557 2.03e-13 ***
## category_code_LT01_5_count   0.92430    0.06152  15.025  < 2e-16 ***
## category_code_LT01_8_count  -0.12719    0.26940  -0.472    0.637    
## category_code_LT01_12_count  0.02465    0.20281   0.122    0.903    
## category_code_LT01_16_count  0.45067    1.15003   0.392    0.695    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.6406, Adjusted R-squared:  0.6362 
## F-statistic: 145.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 0.636160822996974 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9857 -0.7499  0.0426  0.8356  3.4591 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96032    0.08589 115.963  < 2e-16 ***
## category_code_LT01_2_count   0.54679    0.08764   6.239 9.53e-10 ***
## category_code_LT01_4_count   0.68492    0.09218   7.430 4.84e-13 ***
## category_code_LT01_5_count   0.92402    0.06161  14.998  < 2e-16 ***
## category_code_LT01_8_count  -0.11699    0.26934  -0.434    0.664    
## category_code_LT01_13_count  0.06316    0.23922   0.264    0.792    
## category_code_LT01_14_count  0.04130    0.32159   0.128    0.898    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6406, Adjusted R-squared:  0.6362 
## F-statistic: 145.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 0.636150968466915 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9858 -0.7494  0.0359  0.8449  3.4587 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95983    0.08580 116.082  < 2e-16 ***
## category_code_LT01_2_count   0.54705    0.08774   6.235 9.74e-10 ***
## category_code_LT01_4_count   0.68608    0.09168   7.483 3.38e-13 ***
## category_code_LT01_5_count   0.92484    0.06133  15.080  < 2e-16 ***
## category_code_LT01_8_count  -0.11660    0.26933  -0.433    0.665    
## category_code_LT01_13_count  0.06395    0.23972   0.267    0.790    
## category_code_LT01_15_count  0.04170    0.73744   0.057    0.955    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6362 
## F-statistic: 145.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 0.636266899628077 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9858 -0.7498  0.0350  0.8454  3.4588 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96024    0.08579 116.098  < 2e-16 ***
## category_code_LT01_2_count   0.54312    0.08816   6.161 1.51e-09 ***
## category_code_LT01_4_count   0.68774    0.09132   7.531 2.43e-13 ***
## category_code_LT01_5_count   0.92437    0.06132  15.075  < 2e-16 ***
## category_code_LT01_8_count  -0.12174    0.26960  -0.452    0.652    
## category_code_LT01_13_count  0.06656    0.23934   0.278    0.781    
## category_code_LT01_16_count  0.45977    1.15053   0.400    0.690    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.6407, Adjusted R-squared:  0.6363 
## F-statistic: 145.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 0.636110253668536 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9862 -0.7500  0.0488  0.8352  3.4584 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96041    0.08590 115.955  < 2e-16 ***
## category_code_LT01_2_count   0.54770    0.08774   6.242 9.33e-10 ***
## category_code_LT01_4_count   0.68708    0.09205   7.464 3.84e-13 ***
## category_code_LT01_5_count   0.92460    0.06159  15.012  < 2e-16 ***
## category_code_LT01_8_count  -0.12119    0.26894  -0.451    0.652    
## category_code_LT01_14_count  0.04096    0.32162   0.127    0.899    
## category_code_LT01_15_count  0.02822    0.73596   0.038    0.969    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6361 
## F-statistic: 145.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 0.636226188524494 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9863 -0.7505  0.0429  0.8361  3.4585 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96092    0.08589 115.967  < 2e-16 ***
## category_code_LT01_2_count   0.54362    0.08820   6.164 1.48e-09 ***
## category_code_LT01_4_count   0.68840    0.09173   7.504 2.93e-13 ***
## category_code_LT01_5_count   0.92404    0.06158  15.005  < 2e-16 ***
## category_code_LT01_8_count  -0.12663    0.26924  -0.470    0.638    
## category_code_LT01_14_count  0.04818    0.32206   0.150    0.881    
## category_code_LT01_16_count  0.45769    1.15162   0.397    0.691    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.6406, Adjusted R-squared:  0.6362 
## F-statistic: 145.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 0.636211717762802 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9864 -0.7499  0.0325  0.8425  3.4580 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96033    0.08580 116.088  < 2e-16 ***
## category_code_LT01_2_count   0.54408    0.08826   6.164 1.48e-09 ***
## category_code_LT01_4_count   0.68987    0.09120   7.564 1.93e-13 ***
## category_code_LT01_5_count   0.92500    0.06130  15.090  < 2e-16 ***
## category_code_LT01_8_count  -0.12611    0.26923  -0.468    0.640    
## category_code_LT01_15_count  0.03927    0.73630   0.053    0.957    
## category_code_LT01_16_count  0.45030    1.15059   0.391    0.696    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.6406, Adjusted R-squared:  0.6362 
## F-statistic: 145.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.641137338709107 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9606 -0.7347  0.0459  0.8739  3.4019 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94519    0.08842 112.476  < 2e-16 ***
## category_code_LT01_2_count   0.45086    0.09529   4.732 2.92e-06 ***
## category_code_LT01_4_count   0.60368    0.09688   6.231 9.98e-10 ***
## category_code_LT01_5_count   0.90964    0.06037  15.068  < 2e-16 ***
## category_code_LT01_9_count   0.31549    0.22179   1.422   0.1555    
## category_code_LT01_10_count  0.08016    0.11026   0.727   0.4675    
## category_code_LT01_11_count  0.22879    0.11636   1.966   0.0498 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.349 on 491 degrees of freedom
## Multiple R-squared:  0.6455, Adjusted R-squared:  0.6411 
## F-statistic:   149 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 0.638314954967476 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9548 -0.7305  0.0667  0.8720  3.4007 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93697    0.08867 112.069  < 2e-16 ***
## category_code_LT01_2_count   0.52166    0.08931   5.841 9.47e-09 ***
## category_code_LT01_4_count   0.67019    0.09139   7.334 9.32e-13 ***
## category_code_LT01_5_count   0.91309    0.06083  15.009  < 2e-16 ***
## category_code_LT01_9_count   0.33672    0.22239   1.514    0.131    
## category_code_LT01_10_count  0.08534    0.11073   0.771    0.441    
## category_code_LT01_12_count  0.01292    0.20218   0.064    0.949    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6427, Adjusted R-squared:  0.6383 
## F-statistic: 147.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 0.638411938169673 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9547 -0.7298  0.0529  0.8751  3.4021 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93714    0.08866 112.084  < 2e-16 ***
## category_code_LT01_2_count   0.52071    0.08851   5.883 7.47e-09 ***
## category_code_LT01_4_count   0.66721    0.09152   7.290 1.25e-12 ***
## category_code_LT01_5_count   0.91280    0.06059  15.064  < 2e-16 ***
## category_code_LT01_9_count   0.34230    0.22288   1.536    0.125    
## category_code_LT01_10_count  0.08419    0.11070   0.760    0.447    
## category_code_LT01_13_count  0.08796    0.23872   0.368    0.713    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.354 on 491 degrees of freedom
## Multiple R-squared:  0.6428, Adjusted R-squared:  0.6384 
## F-statistic: 147.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 0.638326518427615 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9543 -0.7311  0.0627  0.8691  3.3968 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93566    0.08913 111.469  < 2e-16 ***
## category_code_LT01_2_count   0.52280    0.08842   5.912 6.32e-09 ***
## category_code_LT01_4_count   0.67229    0.09175   7.327 9.73e-13 ***
## category_code_LT01_5_count   0.91427    0.06086  15.023  < 2e-16 ***
## category_code_LT01_9_count   0.33792    0.22256   1.518    0.130    
## category_code_LT01_10_count  0.08885    0.11305   0.786    0.432    
## category_code_LT01_14_count -0.04616    0.32819  -0.141    0.888    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.354 on 491 degrees of freedom
## Multiple R-squared:  0.6427, Adjusted R-squared:  0.6383 
## F-statistic: 147.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 0.638312047799896 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9550 -0.7309  0.0663  0.8719  3.4001 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93697    0.08870 112.032  < 2e-16 ***
## category_code_LT01_2_count   0.52241    0.08857   5.898 6.84e-09 ***
## category_code_LT01_4_count   0.67060    0.09137   7.339 8.97e-13 ***
## category_code_LT01_5_count   0.91346    0.06058  15.078  < 2e-16 ***
## category_code_LT01_9_count   0.33680    0.22252   1.514    0.131    
## category_code_LT01_10_count  0.08549    0.11102   0.770    0.442    
## category_code_LT01_15_count  0.00859    0.73629   0.012    0.991    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6427, Adjusted R-squared:  0.6383 
## F-statistic: 147.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 0.638374279134677 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9553 -0.7307  0.0481  0.8721  3.4011 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93748    0.08868 112.060  < 2e-16 ***
## category_code_LT01_2_count   0.51962    0.08893   5.843 9.35e-09 ***
## category_code_LT01_4_count   0.67173    0.09111   7.373 7.16e-13 ***
## category_code_LT01_5_count   0.91308    0.06058  15.071  < 2e-16 ***
## category_code_LT01_9_count   0.33500    0.22245   1.506    0.133    
## category_code_LT01_10_count  0.08446    0.11071   0.763    0.446    
## category_code_LT01_16_count  0.33344    1.14618   0.291    0.771    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.354 on 491 degrees of freedom
## Multiple R-squared:  0.6427, Adjusted R-squared:  0.6384 
## F-statistic: 147.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.640860883833306 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9797 -0.7523  0.0768  0.8380  3.4700 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96273    0.08531 116.777  < 2e-16 ***
## category_code_LT01_2_count   0.45772    0.09517   4.809 2.02e-06 ***
## category_code_LT01_4_count   0.60724    0.09680   6.273 7.76e-10 ***
## category_code_LT01_5_count   0.91188    0.06062  15.042  < 2e-16 ***
## category_code_LT01_9_count   0.33337    0.22039   1.513    0.131    
## category_code_LT01_11_count  0.24188    0.11977   2.020    0.044 *  
## category_code_LT01_12_count -0.08032    0.20720  -0.388    0.698    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6452, Adjusted R-squared:  0.6409 
## F-statistic: 148.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.640817711971504 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9772 -0.7516  0.0666  0.8458  3.4735 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96206    0.08531 116.775  < 2e-16 ***
## category_code_LT01_2_count   0.45498    0.09513   4.783 2.29e-06 ***
## category_code_LT01_4_count   0.60485    0.09713   6.227 1.02e-09 ***
## category_code_LT01_5_count   0.90933    0.06042  15.050  < 2e-16 ***
## category_code_LT01_9_count   0.33862    0.22089   1.533   0.1259    
## category_code_LT01_11_count  0.22923    0.11651   1.967   0.0497 *  
## category_code_LT01_13_count  0.07190    0.23805   0.302   0.7627    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6452, Adjusted R-squared:  0.6408 
## F-statistic: 148.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.640751107094108 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9777 -0.7518  0.0782  0.8484  3.4728 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.962250   0.085415 116.634  < 2e-16 ***
## category_code_LT01_2_count  0.455928   0.095151   4.792 2.20e-06 ***
## category_code_LT01_4_count  0.607093   0.097570   6.222 1.05e-09 ***
## category_code_LT01_5_count  0.909752   0.060679  14.993  < 2e-16 ***
## category_code_LT01_9_count  0.333963   0.220838   1.512   0.1311    
## category_code_LT01_11_count 0.230903   0.116391   1.984   0.0478 *  
## category_code_LT01_14_count 0.004408   0.320141   0.014   0.9890    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6451, Adjusted R-squared:  0.6408 
## F-statistic: 148.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.640751139199601 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9777 -0.7518  0.0780  0.8481  3.4728 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96219    0.08532 116.767  < 2e-16 ***
## category_code_LT01_2_count   0.45605    0.09518   4.791 2.20e-06 ***
## category_code_LT01_4_count   0.60736    0.09703   6.259 8.44e-10 ***
## category_code_LT01_5_count   0.90982    0.06041  15.060  < 2e-16 ***
## category_code_LT01_9_count   0.33406    0.22049   1.515    0.130    
## category_code_LT01_11_count  0.23099    0.11651   1.983    0.048 *  
## category_code_LT01_15_count -0.01119    0.73215  -0.015    0.988    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6451, Adjusted R-squared:  0.6408 
## F-statistic: 148.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.640832958471817 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9778 -0.7514  0.0802  0.8558  3.4729 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96255    0.08531 116.776  < 2e-16 ***
## category_code_LT01_2_count   0.45251    0.09563   4.732 2.91e-06 ***
## category_code_LT01_4_count   0.60830    0.09685   6.281 7.42e-10 ***
## category_code_LT01_5_count   0.90940    0.06041  15.054  < 2e-16 ***
## category_code_LT01_9_count   0.33185    0.22050   1.505   0.1330    
## category_code_LT01_11_count  0.23122    0.11638   1.987   0.0475 *  
## category_code_LT01_16_count  0.38220    1.14161   0.335   0.7379    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.35 on 491 degrees of freedom
## Multiple R-squared:  0.6452, Adjusted R-squared:  0.6408 
## F-statistic: 148.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 0.63799109908593 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9723 -0.7444  0.0620  0.8732  3.4771 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95488    0.08557 116.338  < 2e-16 ***
## category_code_LT01_2_count   0.52558    0.08916   5.895 6.99e-09 ***
## category_code_LT01_4_count   0.67072    0.09175   7.310 1.09e-12 ***
## category_code_LT01_5_count   0.91253    0.06088  14.988  < 2e-16 ***
## category_code_LT01_9_count   0.36240    0.22142   1.637    0.102    
## category_code_LT01_12_count  0.01675    0.20219   0.083    0.934    
## category_code_LT01_13_count  0.09376    0.23878   0.393    0.695    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6424, Adjusted R-squared:  0.638 
## F-statistic:   147 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 0.637877582250907 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9728 -0.7459  0.0596  0.8647  3.4764 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.955048   0.085683 116.184  < 2e-16 ***
## category_code_LT01_2_count  0.527413   0.089101   5.919 6.08e-09 ***
## category_code_LT01_4_count  0.674258   0.092034   7.326 9.79e-13 ***
## category_code_LT01_5_count  0.913098   0.061114  14.941  < 2e-16 ***
## category_code_LT01_9_count  0.356589   0.221424   1.610    0.108    
## category_code_LT01_12_count 0.018366   0.202650   0.091    0.928    
## category_code_LT01_14_count 0.004702   0.322180   0.015    0.988    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6422, Adjusted R-squared:  0.6379 
## F-statistic: 146.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 0.63788170929488 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9729 -0.7482  0.0611  0.8650  3.4762 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95502    0.08558 116.322  < 2e-16 ***
## category_code_LT01_2_count   0.52697    0.08928   5.902 6.69e-09 ***
## category_code_LT01_4_count   0.67380    0.09165   7.352 8.25e-13 ***
## category_code_LT01_5_count   0.91324    0.06088  15.002  < 2e-16 ***
## category_code_LT01_9_count   0.35720    0.22106   1.616    0.107    
## category_code_LT01_12_count  0.01892    0.20222   0.094    0.925    
## category_code_LT01_15_count  0.05598    0.73451   0.076    0.939    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6423, Adjusted R-squared:  0.6379 
## F-statistic: 146.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 0.637952557136352 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9729 -0.7449  0.0524  0.8699  3.4765 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95531    0.08558 116.329  < 2e-16 ***
## category_code_LT01_2_count   0.52416    0.08964   5.848 9.11e-09 ***
## category_code_LT01_4_count   0.67547    0.09132   7.396 6.10e-13 ***
## category_code_LT01_5_count   0.91274    0.06088  14.992  < 2e-16 ***
## category_code_LT01_9_count   0.35461    0.22108   1.604    0.109    
## category_code_LT01_12_count  0.01964    0.20218   0.097    0.923    
## category_code_LT01_16_count  0.36591    1.14630   0.319    0.750    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6423, Adjusted R-squared:  0.638 
## F-statistic:   147 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 0.637986356474241 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9726 -0.7446  0.0606  0.8723  3.4766 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.955009   0.085667 116.205  < 2e-16 ***
## category_code_LT01_2_count  0.526576   0.088305   5.963 4.73e-09 ***
## category_code_LT01_4_count  0.671110   0.092240   7.276 1.37e-12 ***
## category_code_LT01_5_count  0.912873   0.060907  14.988  < 2e-16 ***
## category_code_LT01_9_count  0.362206   0.221850   1.633    0.103    
## category_code_LT01_13_count 0.094209   0.238716   0.395    0.693    
## category_code_LT01_14_count 0.006684   0.321368   0.021    0.983    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6424, Adjusted R-squared:  0.638 
## F-statistic:   147 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 0.637993530070938 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9727 -0.7463  0.0599  0.8722  3.4765 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95496    0.08557 116.340  < 2e-16 ***
## category_code_LT01_2_count   0.52600    0.08846   5.946 5.21e-09 ***
## category_code_LT01_4_count   0.67048    0.09184   7.301 1.16e-12 ***
## category_code_LT01_5_count   0.91307    0.06063  15.059  < 2e-16 ***
## category_code_LT01_9_count   0.36314    0.22151   1.639    0.102    
## category_code_LT01_13_count  0.09583    0.23925   0.401    0.689    
## category_code_LT01_15_count  0.07418    0.73586   0.101    0.920    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6424, Adjusted R-squared:  0.638 
## F-statistic:   147 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 0.638067625086484 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9727 -0.7448  0.0543  0.8736  3.4767 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95526    0.08556 116.349  < 2e-16 ***
## category_code_LT01_2_count   0.52323    0.08881   5.892 7.10e-09 ***
## category_code_LT01_4_count   0.67237    0.09145   7.352 8.23e-13 ***
## category_code_LT01_5_count   0.91255    0.06064  15.049  < 2e-16 ***
## category_code_LT01_9_count   0.36041    0.22149   1.627    0.104    
## category_code_LT01_13_count  0.09718    0.23886   0.407    0.684    
## category_code_LT01_16_count  0.38152    1.14677   0.333    0.740    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6424, Adjusted R-squared:  0.6381 
## F-statistic:   147 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 0.637875551655949 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9733 -0.7497  0.0584  0.8730  3.4757 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.955144   0.085681 116.189  < 2e-16 ***
## category_code_LT01_2_count  0.528126   0.088383   5.975 4.41e-09 ***
## category_code_LT01_4_count  0.674322   0.092099   7.322 1.01e-12 ***
## category_code_LT01_5_count  0.913642   0.060898  15.003  < 2e-16 ***
## category_code_LT01_9_count  0.356985   0.221495   1.612    0.108    
## category_code_LT01_14_count 0.006482   0.321432   0.020    0.984    
## category_code_LT01_15_count 0.054267   0.734355   0.074    0.941    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6422, Adjusted R-squared:  0.6379 
## F-statistic: 146.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 0.637946722558446 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9733 -0.7465  0.0512  0.8738  3.4759 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95552    0.08568 116.193  < 2e-16 ***
## category_code_LT01_2_count   0.52528    0.08877   5.917 6.14e-09 ***
## category_code_LT01_4_count   0.67577    0.09178   7.363 7.64e-13 ***
## category_code_LT01_5_count   0.91306    0.06091  14.991  < 2e-16 ***
## category_code_LT01_9_count   0.35415    0.22153   1.599    0.111    
## category_code_LT01_14_count  0.01256    0.32191   0.039    0.969    
## category_code_LT01_16_count  0.36661    1.14801   0.319    0.750    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6423, Adjusted R-squared:  0.6379 
## F-statistic:   147 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 0.637950938876022 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9734 -0.7471  0.0517  0.8744  3.4757 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95540    0.08558 116.330  < 2e-16 ***
## category_code_LT01_2_count   0.52490    0.08889   5.905 6.59e-09 ***
## category_code_LT01_4_count   0.67556    0.09132   7.397 6.06e-13 ***
## category_code_LT01_5_count   0.91336    0.06063  15.066  < 2e-16 ***
## category_code_LT01_9_count   0.35514    0.22114   1.606    0.109    
## category_code_LT01_15_count  0.06251    0.73468   0.085    0.932    
## category_code_LT01_16_count  0.36742    1.14683   0.320    0.749    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.355 on 491 degrees of freedom
## Multiple R-squared:  0.6423, Adjusted R-squared:  0.638 
## F-statistic:   147 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.639792742258227 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9663 -0.7346  0.0461  0.8515  3.3712 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94503    0.08859 112.261  < 2e-16 ***
## category_code_LT01_2_count   0.46622    0.09508   4.904 1.28e-06 ***
## category_code_LT01_4_count   0.61142    0.09691   6.309 6.26e-10 ***
## category_code_LT01_5_count   0.91817    0.06055  15.165  < 2e-16 ***
## category_code_LT01_10_count  0.09972    0.10977   0.908   0.3641    
## category_code_LT01_11_count  0.24891    0.11981   2.078   0.0383 *  
## category_code_LT01_12_count -0.08883    0.20760  -0.428   0.6689    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6441, Adjusted R-squared:  0.6398 
## F-statistic: 148.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.639681434764669 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9644 -0.7344  0.0559  0.8526  3.3763 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94480    0.08860 112.244  < 2e-16 ***
## category_code_LT01_2_count   0.46402    0.09503   4.883 1.42e-06 ***
## category_code_LT01_4_count   0.61022    0.09721   6.278 7.57e-10 ***
## category_code_LT01_5_count   0.91570    0.06034  15.174  < 2e-16 ***
## category_code_LT01_10_count  0.09783    0.10977   0.891   0.3733    
## category_code_LT01_11_count  0.23595    0.11657   2.024   0.0435 *  
## category_code_LT01_13_count  0.04214    0.23797   0.177   0.8595    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.644,  Adjusted R-squared:  0.6397 
## F-statistic: 148.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.639663467230707 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9641 -0.7336  0.0708  0.8530  3.3736 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94399    0.08907 111.644  < 2e-16 ***
## category_code_LT01_2_count   0.46466    0.09504   4.889 1.37e-06 ***
## category_code_LT01_4_count   0.61250    0.09762   6.275 7.71e-10 ***
## category_code_LT01_5_count   0.91644    0.06063  15.115  < 2e-16 ***
## category_code_LT01_10_count  0.10027    0.11225   0.893   0.3721    
## category_code_LT01_11_count  0.23685    0.11647   2.034   0.0425 *  
## category_code_LT01_14_count -0.02713    0.32733  -0.083   0.9340    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.644,  Adjusted R-squared:  0.6397 
## F-statistic:   148 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.639669845901133 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9641 -0.7402  0.0839  0.8527  3.3748 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94449    0.08863 112.208  < 2e-16 ***
## category_code_LT01_2_count   0.46488    0.09507   4.890 1.37e-06 ***
## category_code_LT01_4_count   0.61228    0.09711   6.305 6.42e-10 ***
## category_code_LT01_5_count   0.91579    0.06034  15.177  < 2e-16 ***
## category_code_LT01_10_count  0.09936    0.11006   0.903   0.3671    
## category_code_LT01_11_count  0.23745    0.11656   2.037   0.0422 *  
## category_code_LT01_15_count -0.09170    0.73511  -0.125   0.9008    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.644,  Adjusted R-squared:  0.6397 
## F-statistic:   148 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.639746748363361 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9648 -0.7350  0.0748  0.8528  3.3770 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.94540    0.08861 112.236  < 2e-16 ***
## category_code_LT01_2_count   0.46084    0.09556   4.823 1.89e-06 ***
## category_code_LT01_4_count   0.61262    0.09696   6.318 5.95e-10 ***
## category_code_LT01_5_count   0.91546    0.06034  15.171  < 2e-16 ***
## category_code_LT01_10_count  0.09685    0.10981   0.882   0.3782    
## category_code_LT01_11_count  0.23715    0.11646   2.036   0.0422 *  
## category_code_LT01_16_count  0.39679    1.14364   0.347   0.7288    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.352 on 491 degrees of freedom
## Multiple R-squared:  0.6441, Adjusted R-squared:  0.6397 
## F-statistic: 148.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 0.636677308675815 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9586 -0.7653  0.0494  0.8535  3.3734 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93631    0.08887 111.809  < 2e-16 ***
## category_code_LT01_2_count   0.53792    0.08886   6.053 2.82e-09 ***
## category_code_LT01_4_count   0.67881    0.09173   7.400 5.94e-13 ***
## category_code_LT01_5_count   0.91964    0.06082  15.122  < 2e-16 ***
## category_code_LT01_10_count  0.10422    0.11025   0.945    0.345    
## category_code_LT01_12_count  0.01151    0.20269   0.057    0.955    
## category_code_LT01_13_count  0.06271    0.23879   0.263    0.793    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.6411, Adjusted R-squared:  0.6367 
## F-statistic: 146.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 0.636631734140407 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9583 -0.7677  0.0660  0.8523  3.3704 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93540    0.08934 111.206  < 2e-16 ***
## category_code_LT01_2_count   0.53907    0.08881   6.070 2.56e-09 ***
## category_code_LT01_4_count   0.68208    0.09200   7.414 5.40e-13 ***
## category_code_LT01_5_count   0.92048    0.06107  15.072  < 2e-16 ***
## category_code_LT01_10_count  0.10698    0.11270   0.949    0.343    
## category_code_LT01_12_count  0.01376    0.20305   0.068    0.946    
## category_code_LT01_14_count -0.02830    0.32935  -0.086    0.932    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.641,  Adjusted R-squared:  0.6366 
## F-statistic: 146.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 0.636627355370118 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9586 -0.7668  0.0669  0.8529  3.3721 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93610    0.08890 111.764  < 2e-16 ***
## category_code_LT01_2_count   0.53911    0.08896   6.060 2.71e-09 ***
## category_code_LT01_4_count   0.68141    0.09163   7.436 4.65e-13 ***
## category_code_LT01_5_count   0.91995    0.06081  15.128  < 2e-16 ***
## category_code_LT01_10_count  0.10530    0.11056   0.952    0.341    
## category_code_LT01_12_count  0.01246    0.20272   0.061    0.951    
## category_code_LT01_15_count -0.02826    0.73782  -0.038    0.969    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.641,  Adjusted R-squared:  0.6366 
## F-statistic: 146.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 0.636707485233588 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9590 -0.7639  0.0595  0.8534  3.3738 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93681    0.08888 111.796  < 2e-16 ***
## category_code_LT01_2_count   0.53547    0.08939   5.991 4.05e-09 ***
## category_code_LT01_4_count   0.68220    0.09136   7.467 3.77e-13 ***
## category_code_LT01_5_count   0.91949    0.06082  15.119  < 2e-16 ***
## category_code_LT01_10_count  0.10354    0.11029   0.939    0.348    
## category_code_LT01_12_count  0.01386    0.20266   0.068    0.945    
## category_code_LT01_16_count  0.38054    1.14860   0.331    0.741    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.6411, Adjusted R-squared:  0.6367 
## F-statistic: 146.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 0.636679577873262 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9584 -0.7672  0.0478  0.8525  3.3710 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93557    0.08934 111.213  < 2e-16 ***
## category_code_LT01_2_count   0.53886    0.08799   6.124 1.87e-09 ***
## category_code_LT01_4_count   0.68018    0.09216   7.381 6.78e-13 ***
## category_code_LT01_5_count   0.92043    0.06086  15.123  < 2e-16 ***
## category_code_LT01_10_count  0.10633    0.11271   0.943    0.346    
## category_code_LT01_13_count  0.06283    0.23874   0.263    0.793    
## category_code_LT01_14_count -0.02607    0.32870  -0.079    0.937    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.6411, Adjusted R-squared:  0.6367 
## F-statistic: 146.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 0.636675284419776 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9588 -0.7662  0.0484  0.8530  3.3727 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93624    0.08890 111.771  < 2e-16 ***
## category_code_LT01_2_count   0.53876    0.08812   6.114 1.98e-09 ***
## category_code_LT01_4_count   0.67943    0.09176   7.404 5.78e-13 ***
## category_code_LT01_5_count   0.91993    0.06057  15.188  < 2e-16 ***
## category_code_LT01_10_count  0.10464    0.11053   0.947    0.344    
## category_code_LT01_13_count  0.06265    0.23928   0.262    0.794    
## category_code_LT01_15_count -0.01634    0.73921  -0.022    0.982    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.6411, Adjusted R-squared:  0.6367 
## F-statistic: 146.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 0.636760993986996 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9591 -0.7634  0.0467  0.8535  3.3744 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93694    0.08888 111.804  < 2e-16 ***
## category_code_LT01_2_count   0.53513    0.08854   6.044 2.98e-09 ***
## category_code_LT01_4_count   0.68029    0.09145   7.439 4.56e-13 ***
## category_code_LT01_5_count   0.91946    0.06057  15.180  < 2e-16 ***
## category_code_LT01_10_count  0.10296    0.11025   0.934    0.351    
## category_code_LT01_13_count  0.06630    0.23890   0.278    0.782    
## category_code_LT01_16_count  0.39201    1.14927   0.341    0.733    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.357 on 491 degrees of freedom
## Multiple R-squared:  0.6411, Adjusted R-squared:  0.6368 
## F-statistic: 146.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 0.636629556829983 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9584 -0.7687  0.0645  0.8519  3.3695 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93532    0.08937 111.167  < 2e-16 ***
## category_code_LT01_2_count   0.54014    0.08806   6.134 1.77e-09 ***
## category_code_LT01_4_count   0.68287    0.09203   7.420 5.19e-13 ***
## category_code_LT01_5_count   0.92079    0.06086  15.130  < 2e-16 ***
## category_code_LT01_10_count  0.10751    0.11301   0.951    0.342    
## category_code_LT01_14_count -0.02702    0.32872  -0.082    0.935    
## category_code_LT01_15_count -0.02994    0.73759  -0.041    0.968    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.641,  Adjusted R-squared:  0.6366 
## F-statistic: 146.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 0.636706752631745 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9590 -0.7657  0.0588  0.8527  3.3717 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93621    0.08937 111.184  < 2e-16 ***
## category_code_LT01_2_count   0.53656    0.08850   6.063 2.67e-09 ***
## category_code_LT01_4_count   0.68343    0.09175   7.449 4.26e-13 ***
## category_code_LT01_5_count   0.92025    0.06087  15.119  < 2e-16 ***
## category_code_LT01_10_count  0.10528    0.11281   0.933    0.351    
## category_code_LT01_14_count -0.02000    0.32936  -0.061    0.952    
## category_code_LT01_16_count  0.37464    1.15080   0.326    0.745    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.6411, Adjusted R-squared:  0.6367 
## F-statistic: 146.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 0.636704575187735 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9592 -0.7650  0.0585  0.8530  3.3730 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.93671    0.08891 111.757  < 2e-16 ***
## category_code_LT01_2_count   0.53651    0.08861   6.055 2.80e-09 ***
## category_code_LT01_4_count   0.68293    0.09132   7.478 3.49e-13 ***
## category_code_LT01_5_count   0.91985    0.06056  15.188  < 2e-16 ***
## category_code_LT01_10_count  0.10406    0.11056   0.941    0.347    
## category_code_LT01_15_count -0.02014    0.73803  -0.027    0.978    
## category_code_LT01_16_count  0.37794    1.14926   0.329    0.742    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.358 on 491 degrees of freedom
## Multiple R-squared:  0.6411, Adjusted R-squared:  0.6367 
## F-statistic: 146.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.639217986168715 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9879 -0.7544  0.0771  0.8658  3.4591 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96635    0.08548 116.599  < 2e-16 ***
## category_code_LT01_2_count   0.47304    0.09484   4.988 8.49e-07 ***
## category_code_LT01_4_count   0.61496    0.09712   6.332 5.46e-10 ***
## category_code_LT01_5_count   0.91848    0.06060  15.155  < 2e-16 ***
## category_code_LT01_11_count  0.25043    0.11997   2.087   0.0374 *  
## category_code_LT01_12_count -0.08371    0.20768  -0.403   0.6871    
## category_code_LT01_13_count  0.04869    0.23806   0.205   0.8380    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:  0.6392 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.639200715924966 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9881 -0.7548  0.0795  0.8515  3.4591 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96695    0.08557 116.473  < 2e-16 ***
## category_code_LT01_2_count   0.47301    0.09490   4.985 8.63e-07 ***
## category_code_LT01_4_count   0.61481    0.09764   6.297 6.74e-10 ***
## category_code_LT01_5_count   0.91797    0.06086  15.083  < 2e-16 ***
## category_code_LT01_11_count  0.25157    0.11988   2.098   0.0364 *  
## category_code_LT01_12_count -0.08512    0.20817  -0.409   0.6828    
## category_code_LT01_14_count  0.04346    0.32099   0.135   0.8924    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:  0.6392 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.639190841571756 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9880 -0.7545  0.0768  0.8582  3.4589 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96638    0.08548 116.596  < 2e-16 ***
## category_code_LT01_2_count   0.47387    0.09491   4.993 8.28e-07 ***
## category_code_LT01_4_count   0.61696    0.09704   6.358 4.68e-10 ***
## category_code_LT01_5_count   0.91868    0.06060  15.160  < 2e-16 ***
## category_code_LT01_11_count  0.25184    0.12003   2.098   0.0364 *  
## category_code_LT01_12_count -0.08367    0.20780  -0.403   0.6874    
## category_code_LT01_15_count -0.05134    0.73390  -0.070   0.9443    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6392 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.639290512510075 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9881 -0.7547  0.0787  0.8636  3.4591 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96676    0.08547 116.609  < 2e-16 ***
## category_code_LT01_2_count   0.46953    0.09541   4.921 1.17e-06 ***
## category_code_LT01_4_count   0.61760    0.09686   6.377 4.18e-10 ***
## category_code_LT01_5_count   0.91818    0.06060  15.151  < 2e-16 ***
## category_code_LT01_11_count  0.25153    0.11986   2.098   0.0364 *  
## category_code_LT01_12_count -0.08198    0.20767  -0.395   0.6932    
## category_code_LT01_16_count  0.42878    1.14364   0.375   0.7079    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:  0.6393 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.639107218391037 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9858 -0.7464  0.0801  0.8495  3.4623 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96623    0.08557 116.470  < 2e-16 ***
## category_code_LT01_2_count   0.47081    0.09486   4.963 9.57e-07 ***
## category_code_LT01_4_count   0.61369    0.09794   6.266 8.12e-10 ***
## category_code_LT01_5_count   0.91572    0.06069  15.088  < 2e-16 ***
## category_code_LT01_11_count  0.23896    0.11662   2.049    0.041 *  
## category_code_LT01_13_count  0.04759    0.23808   0.200    0.842    
## category_code_LT01_14_count  0.03464    0.32026   0.108    0.914    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6391 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.639099968811094 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9858 -0.7515  0.0799  0.8446  3.4621 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96579    0.08548 116.588  < 2e-16 ***
## category_code_LT01_2_count   0.47147    0.09486   4.970 9.25e-07 ***
## category_code_LT01_4_count   0.61534    0.09738   6.319 5.91e-10 ***
## category_code_LT01_5_count   0.91633    0.06040  15.172  < 2e-16 ***
## category_code_LT01_11_count  0.23928    0.11674   2.050   0.0409 *  
## category_code_LT01_13_count  0.04680    0.23863   0.196   0.8446    
## category_code_LT01_15_count -0.03149    0.73523  -0.043   0.9659    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6391 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.639209853373704 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9858 -0.7462  0.0793  0.8457  3.4623 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96618    0.08547 116.603  < 2e-16 ***
## category_code_LT01_2_count   0.46708    0.09536   4.898 1.31e-06 ***
## category_code_LT01_4_count   0.61606    0.09715   6.341 5.18e-10 ***
## category_code_LT01_5_count   0.91579    0.06040  15.163  < 2e-16 ***
## category_code_LT01_11_count  0.23926    0.11660   2.052   0.0407 *  
## category_code_LT01_13_count  0.05111    0.23823   0.215   0.8302    
## category_code_LT01_16_count  0.44530    1.14451   0.389   0.6974    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6436, Adjusted R-squared:  0.6392 
## F-statistic: 147.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.63908023527466 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9860 -0.7528  0.0822  0.8567  3.4620 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96627    0.08557 116.467  < 2e-16 ***
## category_code_LT01_2_count   0.47157    0.09491   4.968 9.34e-07 ***
## category_code_LT01_4_count   0.61557    0.09785   6.291 6.99e-10 ***
## category_code_LT01_5_count   0.91593    0.06069  15.092  < 2e-16 ***
## category_code_LT01_11_count  0.24028    0.11662   2.060   0.0399 *  
## category_code_LT01_14_count  0.03452    0.32028   0.108   0.9142    
## category_code_LT01_15_count -0.04182    0.73360  -0.057   0.9546    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6434, Adjusted R-squared:  0.6391 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.639188151417894 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9861 -0.7464  0.0822  0.8575  3.4622 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96675    0.08557 116.479  < 2e-16 ***
## category_code_LT01_2_count   0.46709    0.09544   4.894 1.34e-06 ***
## category_code_LT01_4_count   0.61607    0.09766   6.308 6.30e-10 ***
## category_code_LT01_5_count   0.91531    0.06070  15.080  < 2e-16 ***
## category_code_LT01_11_count  0.24026    0.11649   2.062   0.0397 *  
## category_code_LT01_14_count  0.04118    0.32070   0.128   0.8979    
## category_code_LT01_16_count  0.44376    1.14539   0.387   0.6986    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6392 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.639177388805481 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9861 -0.7524  0.0813  0.8560  3.4619 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96622    0.08547 116.598  < 2e-16 ***
## category_code_LT01_2_count   0.46793    0.09542   4.904 1.28e-06 ***
## category_code_LT01_4_count   0.61794    0.09708   6.365 4.47e-10 ***
## category_code_LT01_5_count   0.91605    0.06039  15.168  < 2e-16 ***
## category_code_LT01_11_count  0.24057    0.11660   2.063   0.0396 *  
## category_code_LT01_15_count -0.03149    0.73393  -0.043   0.9658    
## category_code_LT01_16_count  0.43399    1.14438   0.379   0.7047    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.353 on 491 degrees of freedom
## Multiple R-squared:  0.6435, Adjusted R-squared:  0.6392 
## F-statistic: 147.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.636026067516974 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9813 -0.7486  0.0463  0.8372  3.4653 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95904    0.08587 115.984  < 2e-16 ***
## category_code_LT01_2_count   0.54584    0.08858   6.162 1.50e-09 ***
## category_code_LT01_4_count   0.68322    0.09243   7.392 6.29e-13 ***
## category_code_LT01_5_count   0.91955    0.06114  15.041  < 2e-16 ***
## category_code_LT01_12_count  0.01675    0.20322   0.082    0.934    
## category_code_LT01_13_count  0.06868    0.23893   0.287    0.774    
## category_code_LT01_14_count  0.03741    0.32238   0.116    0.908    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.636 
## F-statistic: 145.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.636018330319754 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9813 -0.7481  0.0395  0.8388  3.4649 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95859    0.08577 116.105  < 2e-16 ***
## category_code_LT01_2_count   0.54592    0.08874   6.152 1.59e-09 ***
## category_code_LT01_4_count   0.68418    0.09202   7.435 4.69e-13 ***
## category_code_LT01_5_count   0.92026    0.06087  15.118  < 2e-16 ***
## category_code_LT01_12_count  0.01862    0.20279   0.092    0.927    
## category_code_LT01_13_count  0.06938    0.23943   0.290    0.772    
## category_code_LT01_15_count  0.04059    0.73772   0.055    0.956    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.636 
## F-statistic: 145.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.63612273895724 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9812 -0.7485  0.0391  0.8410  3.4653 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95893    0.08576 116.119  < 2e-16 ***
## category_code_LT01_2_count   0.54215    0.08916   6.081 2.41e-09 ***
## category_code_LT01_4_count   0.68567    0.09163   7.483 3.38e-13 ***
## category_code_LT01_5_count   0.91962    0.06088  15.106  < 2e-16 ***
## category_code_LT01_12_count  0.01957    0.20273   0.097    0.923    
## category_code_LT01_13_count  0.07206    0.23907   0.301    0.763    
## category_code_LT01_16_count  0.43608    1.14952   0.379    0.705    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6361 
## F-statistic: 145.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.63596574185318 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9816 -0.7486  0.0441  0.8368  3.4648 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95908    0.08587 115.974  < 2e-16 ***
## category_code_LT01_2_count   0.54677    0.08871   6.164 1.48e-09 ***
## category_code_LT01_4_count   0.68553    0.09235   7.424 5.07e-13 ***
## category_code_LT01_5_count   0.91998    0.06113  15.049  < 2e-16 ***
## category_code_LT01_12_count  0.01826    0.20324   0.090    0.928    
## category_code_LT01_14_count  0.03680    0.32242   0.114    0.909    
## category_code_LT01_15_count  0.02592    0.73626   0.035    0.972    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.636 
## F-statistic: 145.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.636068820518852 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9816 -0.7491  0.0439  0.8377  3.4651 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95950    0.08587 115.985  < 2e-16 ***
## category_code_LT01_2_count   0.54289    0.08916   6.089 2.30e-09 ***
## category_code_LT01_4_count   0.68670    0.09201   7.463 3.88e-13 ***
## category_code_LT01_5_count   0.91927    0.06114  15.034  < 2e-16 ***
## category_code_LT01_12_count  0.01906    0.20317   0.094    0.925    
## category_code_LT01_14_count  0.04342    0.32283   0.134    0.893    
## category_code_LT01_16_count  0.43091    1.15040   0.375    0.708    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6361 
## F-statistic: 145.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.636057223534096 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9816 -0.7485  0.0354  0.8464  3.4647 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95898    0.08577 116.108  < 2e-16 ***
## category_code_LT01_2_count   0.54315    0.08930   6.083 2.38e-09 ***
## category_code_LT01_4_count   0.68793    0.09156   7.513 2.75e-13 ***
## category_code_LT01_5_count   0.92009    0.06087  15.115  < 2e-16 ***
## category_code_LT01_12_count  0.02115    0.20276   0.104    0.917    
## category_code_LT01_15_count  0.03640    0.73660   0.049    0.961    
## category_code_LT01_16_count  0.42461    1.14948   0.369    0.712    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6361 
## F-statistic: 145.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.636023043858934 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9817 -0.7487  0.0397  0.8368  3.4647 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95912    0.08586 115.988  < 2e-16 ***
## category_code_LT01_2_count   0.54657    0.08787   6.220 1.06e-09 ***
## category_code_LT01_4_count   0.68336    0.09255   7.384 6.64e-13 ***
## category_code_LT01_5_count   0.92003    0.06092  15.101  < 2e-16 ***
## category_code_LT01_13_count  0.06994    0.23938   0.292    0.770    
## category_code_LT01_14_count  0.03911    0.32163   0.122    0.903    
## category_code_LT01_15_count  0.03843    0.73757   0.052    0.958    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6404, Adjusted R-squared:  0.636 
## F-statistic: 145.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.636130992275629 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9816 -0.7478  0.0397  0.8378  3.4651 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95955    0.08586 116.000  < 2e-16 ***
## category_code_LT01_2_count   0.54267    0.08833   6.144 1.67e-09 ***
## category_code_LT01_4_count   0.68461    0.09217   7.428 4.93e-13 ***
## category_code_LT01_5_count   0.91928    0.06093  15.087  < 2e-16 ***
## category_code_LT01_13_count  0.07277    0.23902   0.304    0.761    
## category_code_LT01_14_count  0.04606    0.32206   0.143    0.886    
## category_code_LT01_16_count  0.44341    1.15111   0.385    0.700    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6361 
## F-statistic: 145.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.636119198541267 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9817 -0.7486  0.0301  0.8487  3.4646 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95901    0.08576 116.120  < 2e-16 ***
## category_code_LT01_2_count   0.54298    0.08842   6.141 1.69e-09 ***
## category_code_LT01_4_count   0.68586    0.09168   7.481 3.43e-13 ***
## category_code_LT01_5_count   0.92023    0.06062  15.179  < 2e-16 ***
## category_code_LT01_13_count  0.07364    0.23955   0.307    0.759    
## category_code_LT01_15_count  0.04974    0.73798   0.067    0.946    
## category_code_LT01_16_count  0.43729    1.15021   0.380    0.704    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6361 
## F-statistic: 145.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.636063875435392 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9820 -0.7492  0.0357  0.8373  3.4644 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95960    0.08587 115.989  < 2e-16 ***
## category_code_LT01_2_count   0.54382    0.08843   6.150 1.61e-09 ***
## category_code_LT01_4_count   0.68702    0.09206   7.463 3.88e-13 ***
## category_code_LT01_5_count   0.91980    0.06093  15.097  < 2e-16 ***
## category_code_LT01_14_count  0.04539    0.32209   0.141    0.888    
## category_code_LT01_15_count  0.03395    0.73640   0.046    0.963    
## category_code_LT01_16_count  0.43139    1.15101   0.375    0.708    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.359 on 491 degrees of freedom
## Multiple R-squared:  0.6405, Adjusted R-squared:  0.6361 
## F-statistic: 145.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 0.61893379069934 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0198 -0.7917  0.0061  0.9802  3.8251 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97590    0.08784 113.570  < 2e-16 ***
## category_code_LT01_2_count  0.76804    0.07723   9.944  < 2e-16 ***
## category_code_LT01_5_count  0.95080    0.06262  15.183  < 2e-16 ***
## category_code_LT01_6_count  0.49345    0.15179   3.251  0.00123 ** 
## category_code_LT01_7_count  0.61526    0.15160   4.059 5.75e-05 ***
## category_code_LT01_8_count -0.17066    0.27568  -0.619  0.53616    
## category_code_LT01_9_count  0.36021    0.22768   1.582  0.11427    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 0.617252516637863 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.7888 -0.0296  0.9806  3.8352 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96574    0.09119 109.282  < 2e-16 ***
## category_code_LT01_2_count   0.78551    0.07650  10.267  < 2e-16 ***
## category_code_LT01_5_count   0.95787    0.06261  15.299  < 2e-16 ***
## category_code_LT01_6_count   0.49219    0.15383   3.200  0.00147 ** 
## category_code_LT01_7_count   0.63373    0.15158   4.181 3.44e-05 ***
## category_code_LT01_8_count  -0.15981    0.27619  -0.579  0.56312    
## category_code_LT01_10_count  0.06639    0.11465   0.579  0.56283    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 0.623334965737512 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0286 -0.7387 -0.0040  0.9214  3.8141 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98690    0.08734 114.349  < 2e-16 ***
## category_code_LT01_2_count   0.65271    0.08930   7.309  1.1e-12 ***
## category_code_LT01_5_count   0.94752    0.06221  15.231  < 2e-16 ***
## category_code_LT01_6_count   0.43083    0.15296   2.817  0.00505 ** 
## category_code_LT01_7_count   0.51024    0.15660   3.258  0.00120 ** 
## category_code_LT01_8_count  -0.13405    0.27407  -0.489  0.62500    
## category_code_LT01_11_count  0.33920    0.11795   2.876  0.00421 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6279, Adjusted R-squared:  0.6233 
## F-statistic: 138.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 0.617067074862144 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0270 -0.7845 -0.0282  0.9775  3.8214 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97951    0.08802 113.373  < 2e-16 ***
## category_code_LT01_2_count   0.78468    0.07769  10.100  < 2e-16 ***
## category_code_LT01_5_count   0.95599    0.06286  15.208  < 2e-16 ***
## category_code_LT01_6_count   0.50086    0.15291   3.275  0.00113 ** 
## category_code_LT01_7_count   0.64043    0.15110   4.238 2.69e-05 ***
## category_code_LT01_8_count  -0.16032    0.27639  -0.580  0.56214    
## category_code_LT01_12_count  0.06508    0.20859   0.312  0.75518    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 0.61712801884097 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0272 -0.7808 -0.0219  0.9750  3.8217 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97926    0.08802 113.375  < 2e-16 ***
## category_code_LT01_2_count   0.78637    0.07656  10.271  < 2e-16 ***
## category_code_LT01_5_count   0.95665    0.06267  15.265  < 2e-16 ***
## category_code_LT01_6_count   0.50637    0.15194   3.333 0.000925 ***
## category_code_LT01_7_count   0.63231    0.15252   4.146 3.99e-05 ***
## category_code_LT01_8_count  -0.15035    0.27670  -0.543 0.587135    
## category_code_LT01_13_count  0.10325    0.24646   0.419 0.675444    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 0.617759958764175 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0259 -0.7809 -0.0042  0.9697  3.8184 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98257    0.08799 113.446  < 2e-16 ***
## category_code_LT01_2_count   0.77579    0.07738  10.026  < 2e-16 ***
## category_code_LT01_5_count   0.94995    0.06305  15.067  < 2e-16 ***
## category_code_LT01_6_count   0.51759    0.15224   3.400 0.000729 ***
## category_code_LT01_7_count   0.62620    0.15169   4.128  4.3e-05 ***
## category_code_LT01_8_count  -0.16227    0.27602  -0.588 0.556859    
## category_code_LT01_14_count  0.32678    0.32884   0.994 0.320832    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6224, Adjusted R-squared:  0.6178 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 0.617221730238982 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0287 -0.7820 -0.0341  0.9737  3.8212 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97976    0.08801 113.399  < 2e-16 ***
## category_code_LT01_2_count   0.78389    0.07688  10.196  < 2e-16 ***
## category_code_LT01_5_count   0.95799    0.06262  15.300  < 2e-16 ***
## category_code_LT01_6_count   0.50148    0.15217   3.296  0.00105 ** 
## category_code_LT01_7_count   0.64224    0.15107   4.251 2.54e-05 ***
## category_code_LT01_8_count  -0.15911    0.27619  -0.576  0.56482    
## category_code_LT01_15_count  0.40963    0.75322   0.544  0.58680    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6172 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 0.617229250140975 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0281 -0.7817 -0.0226  0.9723  3.8209 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98002    0.08801 113.399  < 2e-16 ***
## category_code_LT01_2_count   0.78239    0.07725  10.128  < 2e-16 ***
## category_code_LT01_5_count   0.95684    0.06263  15.277  < 2e-16 ***
## category_code_LT01_6_count   0.51460    0.15267   3.371 0.000809 ***
## category_code_LT01_7_count   0.64278    0.15108   4.254 2.51e-05 ***
## category_code_LT01_8_count  -0.16585    0.27659  -0.600 0.549047    
## category_code_LT01_16_count  0.65483    1.18491   0.553 0.580761    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6172 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 0.618764622493593 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0049 -0.7861  0.0202  0.9710  3.8363 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96463    0.09098 109.521  < 2e-16 ***
## category_code_LT01_2_count   0.76707    0.07740   9.910  < 2e-16 ***
## category_code_LT01_5_count   0.94548    0.06199  15.253  < 2e-16 ***
## category_code_LT01_6_count   0.47989    0.15350   3.126  0.00188 ** 
## category_code_LT01_7_count   0.60766    0.15195   3.999 7.34e-05 ***
## category_code_LT01_9_count   0.34595    0.22893   1.511  0.13139    
## category_code_LT01_10_count  0.04677    0.11507   0.406  0.68459    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6234, Adjusted R-squared:  0.6188 
## F-statistic: 135.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 0.624776325477615 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0160 -0.7823  0.0454  0.9318  3.8190 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98200    0.08717 114.515  < 2e-16 ***
## category_code_LT01_2_count   0.63613    0.08985   7.080 5.02e-12 ***
## category_code_LT01_5_count   0.93650    0.06157  15.211  < 2e-16 ***
## category_code_LT01_6_count   0.41677    0.15265   2.730  0.00656 ** 
## category_code_LT01_7_count   0.48575    0.15682   3.097  0.00206 ** 
## category_code_LT01_9_count   0.32956    0.22601   1.458  0.14544    
## category_code_LT01_11_count  0.33384    0.11778   2.835  0.00478 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 0.618700853229065 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0131 -0.8038  0.0041  0.9824  3.8268 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97420    0.08783 113.565  < 2e-16 ***
## category_code_LT01_2_count   0.76490    0.07864   9.726  < 2e-16 ***
## category_code_LT01_5_count   0.94355    0.06225  15.158  < 2e-16 ***
## category_code_LT01_6_count   0.48446    0.15269   3.173   0.0016 ** 
## category_code_LT01_7_count   0.61151    0.15158   4.034 6.35e-05 ***
## category_code_LT01_9_count   0.35571    0.22764   1.563   0.1188    
## category_code_LT01_12_count  0.05995    0.20802   0.288   0.7733    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6233, Adjusted R-squared:  0.6187 
## F-statistic: 135.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 0.61888505462214 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0130 -0.7898  0.0031  0.9888  3.8271 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97384    0.08781 113.584  < 2e-16 ***
## category_code_LT01_2_count   0.76457    0.07764   9.847  < 2e-16 ***
## category_code_LT01_5_count   0.94393    0.06201  15.222  < 2e-16 ***
## category_code_LT01_6_count   0.48956    0.15166   3.228 0.001330 ** 
## category_code_LT01_7_count   0.59984    0.15308   3.919 0.000102 ***
## category_code_LT01_9_count   0.36507    0.22816   1.600 0.110226    
## category_code_LT01_13_count  0.13929    0.24607   0.566 0.571619    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 0.619238290249563 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0124 -0.7801  0.0195  0.9556  3.8239 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97704    0.08782 113.606  < 2e-16 ***
## category_code_LT01_2_count   0.75799    0.07822   9.691  < 2e-16 ***
## category_code_LT01_5_count   0.93848    0.06241  15.037  < 2e-16 ***
## category_code_LT01_6_count   0.49992    0.15206   3.288  0.00108 ** 
## category_code_LT01_7_count   0.59986    0.15210   3.944 9.18e-05 ***
## category_code_LT01_9_count   0.34226    0.22801   1.501  0.13397    
## category_code_LT01_14_count  0.28978    0.32891   0.881  0.37873    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6238, Adjusted R-squared:  0.6192 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 0.618886769671221 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.7872 -0.0016  0.9903  3.8265 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97443    0.08781 113.595  < 2e-16 ***
## category_code_LT01_2_count   0.76335    0.07789   9.800  < 2e-16 ***
## category_code_LT01_5_count   0.94541    0.06197  15.255  < 2e-16 ***
## category_code_LT01_6_count   0.48438    0.15193   3.188  0.00152 ** 
## category_code_LT01_7_count   0.61315    0.15153   4.046 6.04e-05 ***
## category_code_LT01_9_count   0.35835    0.22763   1.574  0.11606    
## category_code_LT01_15_count  0.42694    0.75166   0.568  0.57030    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 0.61880462981984 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0141 -0.7887  0.0096  0.9844  3.8263 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97463    0.08782 113.582  < 2e-16 ***
## category_code_LT01_2_count   0.76359    0.07815   9.771  < 2e-16 ***
## category_code_LT01_5_count   0.94433    0.06201  15.229  < 2e-16 ***
## category_code_LT01_6_count   0.49645    0.15242   3.257   0.0012 ** 
## category_code_LT01_7_count   0.61371    0.15158   4.049 5.98e-05 ***
## category_code_LT01_9_count   0.35211    0.22776   1.546   0.1227    
## category_code_LT01_16_count  0.55002    1.18139   0.466   0.6417    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6234, Adjusted R-squared:  0.6188 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 0.62339564449662 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0108 -0.7360  0.0221  0.9129  3.8287 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97224    0.09047 110.227  < 2e-16 ***
## category_code_LT01_2_count   0.64912    0.08952   7.251 1.62e-12 ***
## category_code_LT01_5_count   0.94311    0.06152  15.330  < 2e-16 ***
## category_code_LT01_6_count   0.41364    0.15465   2.675  0.00773 ** 
## category_code_LT01_7_count   0.49984    0.15694   3.185  0.00154 ** 
## category_code_LT01_10_count  0.06416    0.11371   0.564  0.57286    
## category_code_LT01_11_count  0.34066    0.11789   2.890  0.00403 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6279, Adjusted R-squared:  0.6234 
## F-statistic: 138.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 0.617052131724247 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0085 -0.7867 -0.0174  0.9898  3.8365 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96447    0.09119 109.274  < 2e-16 ***
## category_code_LT01_2_count   0.78228    0.07792  10.040  < 2e-16 ***
## category_code_LT01_5_count   0.95094    0.06221  15.285  < 2e-16 ***
## category_code_LT01_6_count   0.48383    0.15466   3.128  0.00186 ** 
## category_code_LT01_7_count   0.63009    0.15154   4.158 3.79e-05 ***
## category_code_LT01_10_count  0.06461    0.11470   0.563  0.57350    
## category_code_LT01_12_count  0.05812    0.20853   0.279  0.78057    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 0.617142174274184 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0089 -0.7760 -0.0113  0.9955  3.8366 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96438    0.09118 109.286  < 2e-16 ***
## category_code_LT01_2_count   0.78330    0.07682  10.196  < 2e-16 ***
## category_code_LT01_5_count   0.95170    0.06197  15.358  < 2e-16 ***
## category_code_LT01_6_count   0.48911    0.15373   3.182  0.00156 ** 
## category_code_LT01_7_count   0.62173    0.15286   4.067 5.54e-05 ***
## category_code_LT01_10_count  0.06420    0.11468   0.560  0.57586    
## category_code_LT01_13_count  0.10816    0.24607   0.440  0.66047    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 0.61759011868547 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0121 -0.7830  0.0121  0.9618  3.8290 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97195    0.09153 108.950  < 2e-16 ***
## category_code_LT01_2_count   0.77549    0.07746  10.011  < 2e-16 ***
## category_code_LT01_5_count   0.94536    0.06244  15.139  < 2e-16 ***
## category_code_LT01_6_count   0.50367    0.15460   3.258   0.0012 ** 
## category_code_LT01_7_count   0.61968    0.15194   4.079 5.29e-05 ***
## category_code_LT01_10_count  0.04200    0.11765   0.357   0.7213    
## category_code_LT01_14_count  0.29600    0.33764   0.877   0.3811    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6176 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 0.61718247177478 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0107 -0.7757 -0.0256  0.9841  3.8355 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96546    0.09120 109.274  < 2e-16 ***
## category_code_LT01_2_count   0.78167    0.07709  10.140  < 2e-16 ***
## category_code_LT01_5_count   0.95276    0.06194  15.382  < 2e-16 ***
## category_code_LT01_6_count   0.48508    0.15387   3.153  0.00172 ** 
## category_code_LT01_7_count   0.63215    0.15153   4.172 3.57e-05 ***
## category_code_LT01_10_count  0.06101    0.11499   0.531  0.59597    
## category_code_LT01_15_count  0.37383    0.75543   0.495  0.62092    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6172 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 0.617178683532799 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0098 -0.7838 -0.0130  0.9873  3.8356 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96535    0.09119 109.278  < 2e-16 ***
## category_code_LT01_2_count   0.78044    0.07746  10.076  < 2e-16 ***
## category_code_LT01_5_count   0.95154    0.06197  15.355  < 2e-16 ***
## category_code_LT01_6_count   0.49641    0.15455   3.212  0.00141 ** 
## category_code_LT01_7_count   0.63234    0.15154   4.173 3.56e-05 ***
## category_code_LT01_10_count  0.06232    0.11482   0.543  0.58752    
## category_code_LT01_16_count  0.58051    1.18489   0.490  0.62440    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6172 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 0.62328675114868 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0261 -0.7537  0.0021  0.9342  3.8149 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98607    0.08731 114.374  < 2e-16 ***
## category_code_LT01_2_count   0.65411    0.08937   7.319 1.02e-12 ***
## category_code_LT01_5_count   0.94513    0.06173  15.310  < 2e-16 ***
## category_code_LT01_6_count   0.43193    0.15321   2.819  0.00501 ** 
## category_code_LT01_7_count   0.50314    0.15672   3.210  0.00141 ** 
## category_code_LT01_11_count  0.35329    0.12155   2.907  0.00382 ** 
## category_code_LT01_12_count -0.08950    0.21314  -0.420  0.67473    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6278, Adjusted R-squared:  0.6233 
## F-statistic: 138.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 0.623239135908494 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0235 -0.7341  0.0076  0.9371  3.8156 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98540    0.08731 114.363  < 2e-16 ***
## category_code_LT01_2_count   0.65096    0.08946   7.277 1.37e-12 ***
## category_code_LT01_5_count   0.94241    0.06156  15.310  < 2e-16 ***
## category_code_LT01_6_count   0.42782    0.15281   2.800  0.00532 ** 
## category_code_LT01_7_count   0.50063    0.15757   3.177  0.00158 ** 
## category_code_LT01_11_count  0.33927    0.11802   2.875  0.00422 ** 
## category_code_LT01_13_count  0.08256    0.24424   0.338  0.73549    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6278, Adjusted R-squared:  0.6232 
## F-statistic:   138 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 0.623727710861848 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0220 -0.7776  0.0196  0.9098  3.8129 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98809    0.08730 114.413  < 2e-16 ***
## category_code_LT01_2_count   0.64278    0.08999   7.143 3.31e-12 ***
## category_code_LT01_5_count   0.93629    0.06198  15.107  < 2e-16 ***
## category_code_LT01_6_count   0.43792    0.15320   2.858  0.00444 ** 
## category_code_LT01_7_count   0.49562    0.15691   3.159  0.00168 ** 
## category_code_LT01_11_count  0.33649    0.11795   2.853  0.00452 ** 
## category_code_LT01_14_count  0.28313    0.32651   0.867  0.38628    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6283, Adjusted R-squared:  0.6237 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 0.623239966866313 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0244 -0.7348  0.0063  0.9114  3.8153 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98568    0.08731 114.370  < 2e-16 ***
## category_code_LT01_2_count   0.65047    0.08956   7.263 1.49e-12 ***
## category_code_LT01_5_count   0.94324    0.06154  15.328  < 2e-16 ***
## category_code_LT01_6_count   0.42485    0.15296   2.778  0.00569 ** 
## category_code_LT01_7_count   0.50868    0.15656   3.249  0.00124 ** 
## category_code_LT01_11_count  0.33809    0.11821   2.860  0.00442 ** 
## category_code_LT01_15_count  0.25440    0.74907   0.340  0.73429    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6278, Adjusted R-squared:  0.6232 
## F-statistic:   138 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 0.623352937516688 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0238 -0.7344  0.0103  0.9158  3.8150 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98596    0.08730 114.388  < 2e-16 ***
## category_code_LT01_2_count   0.64647    0.09013   7.173 2.72e-12 ***
## category_code_LT01_5_count   0.94198    0.06155  15.303  < 2e-16 ***
## category_code_LT01_6_count   0.43476    0.15349   2.833  0.00481 ** 
## category_code_LT01_7_count   0.50840    0.15647   3.249  0.00124 ** 
## category_code_LT01_11_count  0.34066    0.11790   2.889  0.00403 ** 
## category_code_LT01_16_count  0.60145    1.17358   0.512  0.60854    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6279, Adjusted R-squared:  0.6234 
## F-statistic: 138.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 0.616958417580531 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0211 -0.7915 -0.0082  0.9824  3.8233 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97769    0.08800 113.385  < 2e-16 ***
## category_code_LT01_2_count   0.78281    0.07797  10.040  < 2e-16 ***
## category_code_LT01_5_count   0.95000    0.06224  15.262  < 2e-16 ***
## category_code_LT01_6_count   0.49788    0.15282   3.258   0.0012 ** 
## category_code_LT01_7_count   0.62815    0.15241   4.121 4.42e-05 ***
## category_code_LT01_12_count  0.05814    0.20859   0.279   0.7806    
## category_code_LT01_13_count  0.10929    0.24617   0.444   0.6573    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 0.617524068858625 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0198 -0.7883  0.0082  0.9707  3.8201 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98084    0.08798 113.442  < 2e-16 ***
## category_code_LT01_2_count   0.77394    0.07859   9.847  < 2e-16 ***
## category_code_LT01_5_count   0.94359    0.06262  15.068  < 2e-16 ***
## category_code_LT01_6_count   0.50971    0.15324   3.326 0.000947 ***
## category_code_LT01_7_count   0.62291    0.15165   4.108 4.68e-05 ***
## category_code_LT01_12_count  0.04317    0.20915   0.206 0.836547    
## category_code_LT01_14_count  0.31730    0.33017   0.961 0.337023    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6175 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 0.617034956773974 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0221 -0.7786 -0.0247  0.9780  3.8228 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97811    0.08799 113.404  < 2e-16 ***
## category_code_LT01_2_count   0.78019    0.07835   9.957  < 2e-16 ***
## category_code_LT01_5_count   0.95095    0.06221  15.285  < 2e-16 ***
## category_code_LT01_6_count   0.49232    0.15307   3.216  0.00138 ** 
## category_code_LT01_7_count   0.63836    0.15102   4.227 2.83e-05 ***
## category_code_LT01_12_count  0.06333    0.20852   0.304  0.76146    
## category_code_LT01_15_count  0.40945    0.75353   0.543  0.58712    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.617 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 0.617017452075255 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0214 -0.7944 -0.0057  0.9792  3.8227 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97829    0.08799 113.401  < 2e-16 ***
## category_code_LT01_2_count   0.77922    0.07869   9.903  < 2e-16 ***
## category_code_LT01_5_count   0.94968    0.06225  15.256  < 2e-16 ***
## category_code_LT01_6_count   0.50495    0.15350   3.290  0.00108 ** 
## category_code_LT01_7_count   0.63870    0.15104   4.229  2.8e-05 ***
## category_code_LT01_12_count  0.06177    0.20848   0.296  0.76713    
## category_code_LT01_16_count  0.61812    1.18344   0.522  0.60169    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 0.617652784060352 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0197 -0.7756  0.0176  0.9722  3.8203 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98068    0.08797 113.460  < 2e-16 ***
## category_code_LT01_2_count   0.77348    0.07771   9.954  < 2e-16 ***
## category_code_LT01_5_count   0.94375    0.06244  15.115  < 2e-16 ***
## category_code_LT01_6_count   0.51389    0.15211   3.378 0.000787 ***
## category_code_LT01_7_count   0.61372    0.15301   4.011 6.99e-05 ***
## category_code_LT01_13_count  0.11210    0.24584   0.456 0.648607    
## category_code_LT01_14_count  0.32378    0.32883   0.985 0.325284    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6223, Adjusted R-squared:  0.6177 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 0.617144674282625 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0225 -0.7770 -0.0090  0.9815  3.8230 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97792    0.08798 113.416  < 2e-16 ***
## category_code_LT01_2_count   0.78104    0.07726  10.109  < 2e-16 ***
## category_code_LT01_5_count   0.95178    0.06197  15.359  < 2e-16 ***
## category_code_LT01_6_count   0.49781    0.15204   3.274  0.00113 ** 
## category_code_LT01_7_count   0.62915    0.15237   4.129 4.28e-05 ***
## category_code_LT01_13_count  0.11892    0.24638   0.483  0.62953    
## category_code_LT01_15_count  0.42447    0.75438   0.563  0.57391    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617124212562859 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0218 -0.7893 -0.0061  0.9822  3.8229 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97810    0.08798 113.413  < 2e-16 ***
## category_code_LT01_2_count   0.78001    0.07762  10.050  < 2e-16 ***
## category_code_LT01_5_count   0.95044    0.06201  15.328  < 2e-16 ***
## category_code_LT01_6_count   0.51072    0.15251   3.349 0.000874 ***
## category_code_LT01_7_count   0.62966    0.15238   4.132 4.23e-05 ***
## category_code_LT01_13_count  0.11672    0.24622   0.474 0.635673    
## category_code_LT01_16_count  0.63810    1.18422   0.539 0.590244    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 0.617695198587369 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0210 -0.7899  0.0049  0.9727  3.8199 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98107    0.08796 113.473  < 2e-16 ***
## category_code_LT01_2_count   0.77182    0.07797   9.899  < 2e-16 ***
## category_code_LT01_5_count   0.94497    0.06241  15.142  < 2e-16 ***
## category_code_LT01_6_count   0.50886    0.15237   3.340 0.000902 ***
## category_code_LT01_7_count   0.62437    0.15163   4.118 4.49e-05 ***
## category_code_LT01_14_count  0.31896    0.32892   0.970 0.332660    
## category_code_LT01_15_count  0.38571    0.75295   0.512 0.608697    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6223, Adjusted R-squared:  0.6177 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617757768802048 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0201 -0.7884  0.0155  0.9648  3.8195 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98144    0.08796 113.482  < 2e-16 ***
## category_code_LT01_2_count   0.76893    0.07851   9.794  < 2e-16 ***
## category_code_LT01_5_count   0.94314    0.06245  15.102  < 2e-16 ***
## category_code_LT01_6_count   0.52261    0.15287   3.419 0.000682 ***
## category_code_LT01_7_count   0.62416    0.15161   4.117  4.5e-05 ***
## category_code_LT01_14_count  0.33583    0.32948   1.019 0.308575    
## category_code_LT01_16_count  0.69369    1.18476   0.586 0.558470    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6224, Adjusted R-squared:  0.6178 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617188666941992 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0230 -0.7854 -0.0222  0.9762  3.8224 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97856    0.08797 113.430  < 2e-16 ***
## category_code_LT01_2_count   0.77788    0.07793   9.982  < 2e-16 ***
## category_code_LT01_5_count   0.95160    0.06197  15.356  < 2e-16 ***
## category_code_LT01_6_count   0.50546    0.15272   3.310    0.001 ** 
## category_code_LT01_7_count   0.64057    0.15100   4.242 2.65e-05 ***
## category_code_LT01_15_count  0.41785    0.75361   0.554    0.580    
## category_code_LT01_16_count  0.63687    1.18378   0.538    0.591    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6172 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 0.606537955460793 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0178 -0.8202  0.0183  1.0064  3.8413 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95961    0.09245 107.734  < 2e-16 ***
## category_code_LT01_2_count   0.86855    0.07425  11.698  < 2e-16 ***
## category_code_LT01_5_count   0.97134    0.06343  15.313  < 2e-16 ***
## category_code_LT01_6_count   0.49594    0.15604   3.178  0.00157 ** 
## category_code_LT01_8_count  -0.13651    0.28000  -0.488  0.62610    
## category_code_LT01_9_count   0.44126    0.23153   1.906  0.05725 .  
## category_code_LT01_10_count  0.08111    0.11660   0.696  0.48701    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.413 on 491 degrees of freedom
## Multiple R-squared:  0.6113, Adjusted R-squared:  0.6065 
## F-statistic: 128.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 0.617573514142706 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0316 -0.8120  0.0273  0.9121  3.9107 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98601    0.08803 113.436  < 2e-16 ***
## category_code_LT01_2_count   0.67130    0.08998   7.460 3.95e-13 ***
## category_code_LT01_5_count   0.95317    0.06271  15.200  < 2e-16 ***
## category_code_LT01_6_count   0.41173    0.15426   2.669 0.007858 ** 
## category_code_LT01_8_count  -0.11235    0.27607  -0.407 0.684213    
## category_code_LT01_9_count   0.39763    0.22734   1.749 0.080901 .  
## category_code_LT01_11_count  0.43664    0.11402   3.830 0.000145 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6176 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 0.606253944566589 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0328 -0.8235  0.0089  0.9771  3.8247 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97626    0.08929 111.730  < 2e-16 ***
## category_code_LT01_2_count   0.86798    0.07553  11.492  < 2e-16 ***
## category_code_LT01_5_count   0.96904    0.06370  15.213  < 2e-16 ***
## category_code_LT01_6_count   0.50643    0.15521   3.263  0.00118 ** 
## category_code_LT01_8_count  -0.13719    0.28024  -0.490  0.62468    
## category_code_LT01_9_count   0.45943    0.23009   1.997  0.04641 *  
## category_code_LT01_12_count  0.07606    0.21149   0.360  0.71927    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.413 on 491 degrees of freedom
## Multiple R-squared:  0.611,  Adjusted R-squared:  0.6063 
## F-statistic: 128.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 0.607107250689775 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0306 -0.8154  0.0092  0.9895  3.8257 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97529    0.08920 111.834  < 2e-16 ***
## category_code_LT01_2_count   0.86055    0.07480  11.505  < 2e-16 ***
## category_code_LT01_5_count   0.96720    0.06348  15.235  < 2e-16 ***
## category_code_LT01_6_count   0.51174    0.15406   3.322 0.000961 ***
## category_code_LT01_8_count  -0.11743    0.28016  -0.419 0.675297    
## category_code_LT01_9_count   0.47317    0.23017   2.056 0.040336 *  
## category_code_LT01_13_count  0.27084    0.24765   1.094 0.274657    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.412 on 491 degrees of freedom
## Multiple R-squared:  0.6119, Adjusted R-squared:  0.6071 
## F-statistic:   129 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 0.607376788422057 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0313 -0.8073  0.0232  0.9569  3.8207 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98029    0.08922 111.864  < 2e-16 ***
## category_code_LT01_2_count   0.85463    0.07539  11.337  < 2e-16 ***
## category_code_LT01_5_count   0.96109    0.06387  15.047  < 2e-16 ***
## category_code_LT01_6_count   0.52718    0.15444   3.413 0.000695 ***
## category_code_LT01_8_count  -0.14022    0.27972  -0.501 0.616398    
## category_code_LT01_9_count   0.43764    0.23045   1.899 0.058142 .  
## category_code_LT01_14_count  0.41198    0.33264   1.239 0.216119    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.411 on 491 degrees of freedom
## Multiple R-squared:  0.6121, Adjusted R-squared:  0.6074 
## F-statistic: 129.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 0.60636605498538 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0346 -0.8238  0.0014  0.9882  3.8245 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97649    0.08928 111.749  < 2e-16 ***
## category_code_LT01_2_count   0.86830    0.07461  11.639  < 2e-16 ***
## category_code_LT01_5_count   0.97132    0.06345  15.309  < 2e-16 ***
## category_code_LT01_6_count   0.50807    0.15446   3.289  0.00108 ** 
## category_code_LT01_8_count  -0.13540    0.28005  -0.483  0.62896    
## category_code_LT01_9_count   0.46218    0.23011   2.009  0.04513 *  
## category_code_LT01_15_count  0.39637    0.76392   0.519  0.60409    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.413 on 491 degrees of freedom
## Multiple R-squared:  0.6111, Adjusted R-squared:  0.6064 
## F-statistic: 128.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 0.606276332103741 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0343 -0.8239  0.0099  0.9791  3.8243 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97670    0.08929 111.733  < 2e-16 ***
## category_code_LT01_2_count   0.86892    0.07484  11.611  < 2e-16 ***
## category_code_LT01_5_count   0.97053    0.06347  15.292  < 2e-16 ***
## category_code_LT01_6_count   0.51896    0.15502   3.348 0.000877 ***
## category_code_LT01_8_count  -0.13965    0.28047  -0.498 0.618759    
## category_code_LT01_9_count   0.45681    0.23020   1.984 0.047765 *  
## category_code_LT01_16_count  0.47672    1.20210   0.397 0.691853    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.413 on 491 degrees of freedom
## Multiple R-squared:  0.611,  Adjusted R-squared:  0.6063 
## F-statistic: 128.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 0.61571614813678 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0219 -0.8090  0.0246  0.9273  3.9036 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97079    0.09141 109.076  < 2e-16 ***
## category_code_LT01_2_count   0.68723    0.08962   7.668 9.44e-14 ***
## category_code_LT01_5_count   0.96118    0.06269  15.331  < 2e-16 ***
## category_code_LT01_6_count   0.40394    0.15632   2.584   0.0101 *  
## category_code_LT01_8_count  -0.09942    0.27662  -0.359   0.7194    
## category_code_LT01_10_count  0.09384    0.11452   0.819   0.4130    
## category_code_LT01_11_count  0.44822    0.11405   3.930 9.71e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6204, Adjusted R-squared:  0.6157 
## F-statistic: 133.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 0.603722289752185 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0225 -0.8088 -0.0201  0.9769  3.8420 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95900    0.09278 107.344  < 2e-16 ***
## category_code_LT01_2_count   0.89318    0.07444  11.999  < 2e-16 ***
## category_code_LT01_5_count   0.97898    0.06371  15.367  < 2e-16 ***
## category_code_LT01_6_count   0.50147    0.15740   3.186  0.00153 ** 
## category_code_LT01_8_count  -0.12255    0.28102  -0.436  0.66297    
## category_code_LT01_10_count  0.10560    0.11628   0.908  0.36426    
## category_code_LT01_12_count  0.07282    0.21223   0.343  0.73167    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 491 degrees of freedom
## Multiple R-squared:  0.6085, Adjusted R-squared:  0.6037 
## F-statistic: 127.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 0.604354435009704 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0215 -0.8080 -0.0161  0.9849  3.8421 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95889    0.09270 107.429  < 2e-16 ***
## category_code_LT01_2_count   0.88828    0.07356  12.076  < 2e-16 ***
## category_code_LT01_5_count   0.97781    0.06349  15.400  < 2e-16 ***
## category_code_LT01_6_count   0.50773    0.15636   3.247  0.00124 ** 
## category_code_LT01_8_count  -0.10440    0.28106  -0.371  0.71047    
## category_code_LT01_10_count  0.10268    0.11623   0.883  0.37745    
## category_code_LT01_13_count  0.23589    0.24832   0.950  0.34261    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6091, Adjusted R-squared:  0.6044 
## F-statistic: 127.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 0.604794817559573 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0272 -0.8175  0.0075  0.9514  3.8314 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96958    0.09307 107.114  < 2e-16 ***
## category_code_LT01_2_count   0.88055    0.07424  11.861  < 2e-16 ***
## category_code_LT01_5_count   0.97051    0.06396  15.174  < 2e-16 ***
## category_code_LT01_6_count   0.52813    0.15722   3.359 0.000843 ***
## category_code_LT01_8_count  -0.12519    0.28052  -0.446 0.655585    
## category_code_LT01_10_count  0.07310    0.11937   0.612 0.540542    
## category_code_LT01_14_count  0.41205    0.34213   1.204 0.229022    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 491 degrees of freedom
## Multiple R-squared:  0.6096, Adjusted R-squared:  0.6048 
## F-statistic: 127.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 0.603761769776703 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0247 -0.8060 -0.0171  0.9819  3.8412 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95976    0.09280 107.330  < 2e-16 ***
## category_code_LT01_2_count   0.89472    0.07340  12.190  < 2e-16 ***
## category_code_LT01_5_count   0.98117    0.06346  15.461  < 2e-16 ***
## category_code_LT01_6_count   0.50445    0.15663   3.221  0.00136 ** 
## category_code_LT01_8_count  -0.12034    0.28085  -0.428  0.66849    
## category_code_LT01_10_count  0.10300    0.11657   0.884  0.37737    
## category_code_LT01_15_count  0.31370    0.76844   0.408  0.68329    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 491 degrees of freedom
## Multiple R-squared:  0.6085, Adjusted R-squared:  0.6038 
## F-statistic: 127.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 0.603764064012383 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0241 -0.8106 -0.0207  0.9798  3.8412 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95973    0.09279 107.332  < 2e-16 ***
## category_code_LT01_2_count   0.89361    0.07377  12.113  < 2e-16 ***
## category_code_LT01_5_count   0.98031    0.06347  15.444  < 2e-16 ***
## category_code_LT01_6_count   0.51422    0.15738   3.267  0.00116 ** 
## category_code_LT01_8_count  -0.12546    0.28125  -0.446  0.65573    
## category_code_LT01_10_count  0.10410    0.11640   0.894  0.37157    
## category_code_LT01_16_count  0.49688    1.20692   0.412  0.68074    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 491 degrees of freedom
## Multiple R-squared:  0.6085, Adjusted R-squared:  0.6038 
## F-statistic: 127.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 0.615458979091627 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0439 -0.7832  0.0216  0.9354  3.8314 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99094    0.08824 113.222  < 2e-16 ***
## category_code_LT01_2_count   0.69484    0.08938   7.774 4.51e-14 ***
## category_code_LT01_5_count   0.96379    0.06287  15.329  < 2e-16 ***
## category_code_LT01_6_count   0.43007    0.15494   2.776  0.00572 ** 
## category_code_LT01_8_count  -0.08857    0.27689  -0.320  0.74920    
## category_code_LT01_11_count  0.46719    0.11740   3.979 7.95e-05 ***
## category_code_LT01_12_count -0.12593    0.21517  -0.585  0.55863    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.397 on 491 degrees of freedom
## Multiple R-squared:  0.6201, Adjusted R-squared:  0.6155 
## F-statistic: 133.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 0.615566630587846 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0395 -0.8127  0.0337  0.9349  3.8530 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98974    0.08823 113.221  < 2e-16 ***
## category_code_LT01_2_count   0.68865    0.08959   7.687 8.27e-14 ***
## category_code_LT01_5_count   0.95922    0.06277  15.282  < 2e-16 ***
## category_code_LT01_6_count   0.42469    0.15452   2.748 0.006210 ** 
## category_code_LT01_8_count  -0.08484    0.27702  -0.306 0.759528    
## category_code_LT01_11_count  0.44475    0.11436   3.889 0.000115 ***
## category_code_LT01_13_count  0.17001    0.24535   0.693 0.488688    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6202, Adjusted R-squared:  0.6156 
## F-statistic: 133.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 0.616188871717115 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0385 -0.8035  0.0310  0.9367  3.8506 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99360    0.08820 113.308  < 2e-16 ***
## category_code_LT01_2_count   0.67910    0.09014   7.534 2.39e-13 ***
## category_code_LT01_5_count   0.95218    0.06316  15.076  < 2e-16 ***
## category_code_LT01_6_count   0.43796    0.15492   2.827 0.004889 ** 
## category_code_LT01_8_count  -0.10226    0.27647  -0.370 0.711640    
## category_code_LT01_11_count  0.44179    0.11421   3.868 0.000124 ***
## category_code_LT01_14_count  0.37145    0.32872   1.130 0.259022    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6162 
## F-statistic:   134 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 0.615233251935178 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0418 -0.8157  0.0232  0.9324  3.8494 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99048    0.08826 113.188  < 2e-16 ***
## category_code_LT01_2_count   0.69185    0.08959   7.722 6.46e-14 ***
## category_code_LT01_5_count   0.96141    0.06274  15.323  < 2e-16 ***
## category_code_LT01_6_count   0.42190    0.15474   2.727  0.00663 ** 
## category_code_LT01_8_count  -0.09593    0.27676  -0.347  0.72904    
## category_code_LT01_11_count  0.44918    0.11430   3.930 9.72e-05 ***
## category_code_LT01_15_count  0.17630    0.75662   0.233  0.81585    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.397 on 491 degrees of freedom
## Multiple R-squared:  0.6199, Adjusted R-squared:  0.6152 
## F-statistic: 133.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 0.615361386821055 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0415 -0.8151  0.0317  0.9328  3.8456 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99081    0.08825 113.206  < 2e-16 ***
## category_code_LT01_2_count   0.68767    0.09017   7.626 1.26e-13 ***
## category_code_LT01_5_count   0.96052    0.06274  15.310  < 2e-16 ***
## category_code_LT01_6_count   0.43067    0.15531   2.773  0.00577 ** 
## category_code_LT01_8_count  -0.10223    0.27711  -0.369  0.71235    
## category_code_LT01_11_count  0.45089    0.11405   3.953 8.84e-05 ***
## category_code_LT01_16_count  0.55432    1.18755   0.467  0.64087    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.397 on 491 degrees of freedom
## Multiple R-squared:   0.62,  Adjusted R-squared:  0.6154 
## F-statistic: 133.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 0.603814811124334 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0416 -0.8254 -0.0196  0.9671  3.8207 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98023    0.08954 111.465  < 2e-16 ***
## category_code_LT01_2_count   0.89089    0.07466  11.932  < 2e-16 ***
## category_code_LT01_5_count   0.97601    0.06377  15.304  < 2e-16 ***
## category_code_LT01_6_count   0.52400    0.15544   3.371 0.000808 ***
## category_code_LT01_8_count  -0.10280    0.28139  -0.365 0.715028    
## category_code_LT01_12_count  0.07058    0.21227   0.333 0.739649    
## category_code_LT01_13_count  0.24084    0.24847   0.969 0.332872    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 491 degrees of freedom
## Multiple R-squared:  0.6086, Adjusted R-squared:  0.6038 
## F-statistic: 127.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 0.604540838372006 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0411 -0.8347  0.0004  0.9458  3.8158 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98516    0.08950 111.563  < 2e-16 ***
## category_code_LT01_2_count   0.88037    0.07541  11.674  < 2e-16 ***
## category_code_LT01_5_count   0.96818    0.06414  15.095  < 2e-16 ***
## category_code_LT01_6_count   0.54096    0.15581   3.472 0.000562 ***
## category_code_LT01_8_count  -0.12510    0.28074  -0.446 0.656072    
## category_code_LT01_12_count  0.05190    0.21279   0.244 0.807420    
## category_code_LT01_14_count  0.45360    0.33415   1.357 0.175258    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 491 degrees of freedom
## Multiple R-squared:  0.6093, Adjusted R-squared:  0.6045 
## F-statistic: 127.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 0.60324573501717 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0448 -0.8223 -0.0228  0.9681  3.8198 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98120    0.08960 111.400  < 2e-16 ***
## category_code_LT01_2_count   0.89616    0.07467  12.002  < 2e-16 ***
## category_code_LT01_5_count   0.97924    0.06375  15.361  < 2e-16 ***
## category_code_LT01_6_count   0.51939    0.15582   3.333 0.000923 ***
## category_code_LT01_8_count  -0.11969    0.28117  -0.426 0.670512    
## category_code_LT01_12_count  0.07975    0.21235   0.376 0.707406    
## category_code_LT01_15_count  0.37096    0.76696   0.484 0.628833    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.419 on 491 degrees of freedom
## Multiple R-squared:  0.608,  Adjusted R-squared:  0.6032 
## F-statistic: 126.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 0.603228991764834 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0444 -0.8285 -0.0254  0.9698  3.8195 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98141    0.08960 111.397  < 2e-16 ***
## category_code_LT01_2_count   0.89535    0.07501  11.937  < 2e-16 ***
## category_code_LT01_5_count   0.97829    0.06376  15.342  < 2e-16 ***
## category_code_LT01_6_count   0.53093    0.15631   3.397 0.000738 ***
## category_code_LT01_8_count  -0.12524    0.28158  -0.445 0.656676    
## category_code_LT01_12_count  0.07849    0.21231   0.370 0.711792    
## category_code_LT01_16_count  0.55696    1.20620   0.462 0.644466    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.419 on 491 degrees of freedom
## Multiple R-squared:  0.608,  Adjusted R-squared:  0.6032 
## F-statistic: 126.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 0.605244592652785 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0391 -0.8185 -0.0059  0.9465  3.8165 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98443    0.08943 111.651  < 2e-16 ***
## category_code_LT01_2_count   0.87336    0.07479  11.678  < 2e-16 ***
## category_code_LT01_5_count   0.96631    0.06397  15.105  < 2e-16 ***
## category_code_LT01_6_count   0.54497    0.15456   3.526 0.000462 ***
## category_code_LT01_8_count  -0.10788    0.28076  -0.384 0.700951    
## category_code_LT01_13_count  0.23970    0.24790   0.967 0.334063    
## category_code_LT01_14_count  0.45712    0.33257   1.375 0.169904    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 491 degrees of freedom
## Multiple R-squared:   0.61,  Adjusted R-squared:  0.6052 
## F-statistic:   128 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 0.603953256485027 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0433 -0.8027 -0.0269  0.9709  3.8205 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98045    0.08952 111.487  < 2e-16 ***
## category_code_LT01_2_count   0.89041    0.07382  12.062  < 2e-16 ***
## category_code_LT01_5_count   0.97809    0.06353  15.396  < 2e-16 ***
## category_code_LT01_6_count   0.52515    0.15467   3.395 0.000741 ***
## category_code_LT01_8_count  -0.10057    0.28116  -0.358 0.720717    
## category_code_LT01_13_count  0.25096    0.24867   1.009 0.313384    
## category_code_LT01_15_count  0.40762    0.76728   0.531 0.595479    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6087, Adjusted R-squared:  0.604 
## F-statistic: 127.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 0.60392553201773 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0428 -0.8200 -0.0317  0.9721  3.8203 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98069    0.08953 111.482  < 2e-16 ***
## category_code_LT01_2_count   0.88965    0.07417  11.994  < 2e-16 ***
## category_code_LT01_5_count   0.97705    0.06355  15.375  < 2e-16 ***
## category_code_LT01_6_count   0.53757    0.15521   3.464  0.00058 ***
## category_code_LT01_8_count  -0.10673    0.28155  -0.379  0.70478    
## category_code_LT01_13_count  0.24854    0.24849   1.000  0.31771    
## category_code_LT01_16_count  0.60042    1.20604   0.498  0.61882    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6087, Adjusted R-squared:  0.6039 
## F-statistic: 127.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 0.604651061154676 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0425 -0.8260  0.0070  0.9434  3.8156 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98540    0.08949 111.583  < 2e-16 ***
## category_code_LT01_2_count   0.87966    0.07465  11.784  < 2e-16 ***
## category_code_LT01_5_count   0.96974    0.06395  15.164  < 2e-16 ***
## category_code_LT01_6_count   0.54148    0.15494   3.495 0.000517 ***
## category_code_LT01_8_count  -0.12416    0.28056  -0.443 0.658301    
## category_code_LT01_14_count  0.45727    0.33289   1.374 0.170181    
## category_code_LT01_15_count  0.33930    0.76564   0.443 0.657848    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 491 degrees of freedom
## Multiple R-squared:  0.6094, Adjusted R-squared:  0.6047 
## F-statistic: 127.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 0.604739898430802 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0419 -0.8260  0.0015  0.9394  3.8151 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98584    0.08948 111.594  < 2e-16 ***
## category_code_LT01_2_count   0.87642    0.07525  11.647  < 2e-16 ***
## category_code_LT01_5_count   0.96825    0.06397  15.136  < 2e-16 ***
## category_code_LT01_6_count   0.55452    0.15552   3.566 0.000398 ***
## category_code_LT01_8_count  -0.13161    0.28096  -0.468 0.639678    
## category_code_LT01_14_count  0.47333    0.33352   1.419 0.156483    
## category_code_LT01_16_count  0.66832    1.20661   0.554 0.579911    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 491 degrees of freedom
## Multiple R-squared:  0.6095, Adjusted R-squared:  0.6047 
## F-statistic: 127.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 0.603313364987441 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0463 -0.8179 -0.0174  0.9714  3.8193 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98168    0.08959 111.411  < 2e-16 ***
## category_code_LT01_2_count   0.89615    0.07404  12.104  < 2e-16 ***
## category_code_LT01_5_count   0.98067    0.06351  15.440  < 2e-16 ***
## category_code_LT01_6_count   0.53329    0.15555   3.429 0.000658 ***
## category_code_LT01_8_count  -0.12334    0.28140  -0.438 0.661348    
## category_code_LT01_15_count  0.37669    0.76713   0.491 0.623622    
## category_code_LT01_16_count  0.57210    1.20668   0.474 0.635633    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.419 on 491 degrees of freedom
## Multiple R-squared:  0.6081, Adjusted R-squared:  0.6033 
## F-statistic:   127 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.617745638811486 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0133 -0.7939  0.0308  0.9369  3.9586 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97016    0.09114 109.390  < 2e-16 ***
## category_code_LT01_2_count   0.66752    0.09016   7.403 5.81e-13 ***
## category_code_LT01_5_count   0.94961    0.06200  15.316  < 2e-16 ***
## category_code_LT01_6_count   0.39430    0.15581   2.531 0.011698 *  
## category_code_LT01_9_count   0.37820    0.22862   1.654 0.098705 .  
## category_code_LT01_10_count  0.07148    0.11494   0.622 0.534283    
## category_code_LT01_11_count  0.43616    0.11399   3.826 0.000147 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6224, Adjusted R-squared:  0.6177 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 0.606432718228389 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0122 -0.8237  0.0091  0.9733  3.8424 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95857    0.09243 107.741   <2e-16 ***
## category_code_LT01_2_count   0.86410    0.07580  11.399   <2e-16 ***
## category_code_LT01_5_count   0.96485    0.06302  15.309   <2e-16 ***
## category_code_LT01_6_count   0.48726    0.15686   3.106   0.0020 ** 
## category_code_LT01_9_count   0.43747    0.23144   1.890   0.0593 .  
## category_code_LT01_10_count  0.07935    0.11664   0.680   0.4966    
## category_code_LT01_12_count  0.06893    0.21138   0.326   0.7445    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.413 on 491 degrees of freedom
## Multiple R-squared:  0.6112, Adjusted R-squared:  0.6064 
## F-statistic: 128.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 0.607298497045033 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0114 -0.8110  0.0042  0.9760  3.8423 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95865    0.09233 107.861  < 2e-16 ***
## category_code_LT01_2_count   0.85639    0.07508  11.407  < 2e-16 ***
## category_code_LT01_5_count   0.96347    0.06275  15.354  < 2e-16 ***
## category_code_LT01_6_count   0.49334    0.15576   3.167  0.00163 ** 
## category_code_LT01_9_count   0.45265    0.23160   1.954  0.05121 .  
## category_code_LT01_10_count  0.07509    0.11658   0.644  0.51980    
## category_code_LT01_13_count  0.26983    0.24745   1.090  0.27605    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.411 on 491 degrees of freedom
## Multiple R-squared:  0.612,  Adjusted R-squared:  0.6073 
## F-statistic: 129.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 0.60731833401469 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0167 -0.8160  0.0162  0.9611  3.8328 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96820    0.09275 107.479  < 2e-16 ***
## category_code_LT01_2_count   0.85366    0.07548  11.310  < 2e-16 ***
## category_code_LT01_5_count   0.95741    0.06325  15.137  < 2e-16 ***
## category_code_LT01_6_count   0.51209    0.15673   3.267  0.00116 ** 
## category_code_LT01_9_count   0.42409    0.23150   1.832  0.06757 .  
## category_code_LT01_10_count  0.05047    0.11958   0.422  0.67315    
## category_code_LT01_14_count  0.37621    0.34146   1.102  0.27110    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.411 on 491 degrees of freedom
## Multiple R-squared:  0.6121, Adjusted R-squared:  0.6073 
## F-statistic: 129.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 0.606517732151254 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.8243  0.0015  0.9683  3.8415 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95947    0.09244 107.734  < 2e-16 ***
## category_code_LT01_2_count   0.86467    0.07486  11.551  < 2e-16 ***
## category_code_LT01_5_count   0.96697    0.06274  15.412  < 2e-16 ***
## category_code_LT01_6_count   0.48954    0.15608   3.137  0.00181 ** 
## category_code_LT01_9_count   0.44072    0.23151   1.904  0.05754 .  
## category_code_LT01_10_count  0.07607    0.11695   0.650  0.51569    
## category_code_LT01_15_count  0.35308    0.76605   0.461  0.64507    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.413 on 491 degrees of freedom
## Multiple R-squared:  0.6113, Adjusted R-squared:  0.6065 
## F-statistic: 128.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 0.606438607640006 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0137 -0.8233  0.0111  0.9702  3.8418 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95914    0.09245 107.725  < 2e-16 ***
## category_code_LT01_2_count   0.86529    0.07510  11.522  < 2e-16 ***
## category_code_LT01_5_count   0.96617    0.06277  15.392  < 2e-16 ***
## category_code_LT01_6_count   0.49843    0.15681   3.179  0.00157 ** 
## category_code_LT01_9_count   0.43543    0.23153   1.881  0.06060 .  
## category_code_LT01_10_count  0.07836    0.11674   0.671  0.50242    
## category_code_LT01_16_count  0.40512    1.20154   0.337  0.73614    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.413 on 491 degrees of freedom
## Multiple R-squared:  0.6112, Adjusted R-squared:  0.6064 
## F-statistic: 128.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.617705260828306 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0304 -0.8137  0.0224  0.9289  3.9027 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98554    0.08799 113.491  < 2e-16 ***
## category_code_LT01_2_count   0.67288    0.09001   7.475 3.56e-13 ***
## category_code_LT01_5_count   0.95220    0.06219  15.310  < 2e-16 ***
## category_code_LT01_6_count   0.41549    0.15450   2.689 0.007404 ** 
## category_code_LT01_9_count   0.39268    0.22717   1.729 0.084516 .  
## category_code_LT01_11_count  0.45367    0.11732   3.867 0.000125 ***
## category_code_LT01_12_count -0.12406    0.21438  -0.579 0.563063    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6223, Adjusted R-squared:  0.6177 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.617967944248668 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0256 -0.8045  0.0469  0.9344  3.9276 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98412    0.08796 113.513  < 2e-16 ***
## category_code_LT01_2_count   0.66516    0.09024   7.371 7.26e-13 ***
## category_code_LT01_5_count   0.94724    0.06204  15.269  < 2e-16 ***
## category_code_LT01_6_count   0.41016    0.15402   2.663  0.00800 ** 
## category_code_LT01_9_count   0.40573    0.22750   1.783  0.07513 .  
## category_code_LT01_11_count  0.42987    0.11432   3.760  0.00019 ***
## category_code_LT01_13_count  0.20069    0.24469   0.820  0.41250    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.61822209107625 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0254 -0.8053  0.0248  0.9353  3.9190 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98790    0.08797 113.539  < 2e-16 ***
## category_code_LT01_2_count   0.65961    0.09066   7.276 1.37e-12 ***
## category_code_LT01_5_count   0.94156    0.06245  15.076  < 2e-16 ***
## category_code_LT01_6_count   0.42193    0.15452   2.731 0.006549 ** 
## category_code_LT01_9_count   0.37762    0.22761   1.659 0.097745 .  
## category_code_LT01_11_count  0.43019    0.11414   3.769 0.000184 ***
## category_code_LT01_14_count  0.32865    0.32864   1.000 0.317797    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6228, Adjusted R-squared:  0.6182 
## F-statistic: 135.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.617502446589499 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0281 -0.8194  0.0326  0.9216  3.9223 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98499    0.08800 113.462  < 2e-16 ***
## category_code_LT01_2_count   0.66947    0.09023   7.420 5.21e-13 ***
## category_code_LT01_5_count   0.94957    0.06202  15.310  < 2e-16 ***
## category_code_LT01_6_count   0.40685    0.15427   2.637 0.008625 ** 
## category_code_LT01_9_count   0.39587    0.22728   1.742 0.082176 .  
## category_code_LT01_11_count  0.43556    0.11424   3.813 0.000155 ***
## category_code_LT01_15_count  0.20576    0.75456   0.273 0.785206    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6175 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.617563100771714 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0277 -0.8130  0.0363  0.9228  3.9169 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98525    0.08800 113.470  < 2e-16 ***
## category_code_LT01_2_count   0.66672    0.09073   7.348 8.44e-13 ***
## category_code_LT01_5_count   0.94869    0.06204  15.291  < 2e-16 ***
## category_code_LT01_6_count   0.41469    0.15483   2.678 0.007646 ** 
## category_code_LT01_9_count   0.39134    0.22732   1.722 0.085788 .  
## category_code_LT01_11_count  0.43775    0.11399   3.840 0.000139 ***
## category_code_LT01_16_count  0.46160    1.18303   0.390 0.696569    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6176 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 0.607042439037334 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0253 -0.8234  0.0164  0.9799  3.8269 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97406    0.08916 111.861  < 2e-16 ***
## category_code_LT01_2_count   0.85606    0.07630  11.219  < 2e-16 ***
## category_code_LT01_5_count   0.96143    0.06304  15.252  < 2e-16 ***
## category_code_LT01_6_count   0.50348    0.15493   3.250  0.00123 ** 
## category_code_LT01_9_count   0.46969    0.23008   2.041  0.04174 *  
## category_code_LT01_12_count  0.06500    0.21126   0.308  0.75846    
## category_code_LT01_13_count  0.27392    0.24745   1.107  0.26886    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.412 on 491 degrees of freedom
## Multiple R-squared:  0.6118, Adjusted R-squared:  0.607 
## F-statistic:   129 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 0.607219849841157 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0258 -0.8260  0.0415  0.9627  3.8222 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97879    0.08920 111.873   <2e-16 ***
## category_code_LT01_2_count   0.85195    0.07670  11.107   <2e-16 ***
## category_code_LT01_5_count   0.95527    0.06343  15.060   <2e-16 ***
## category_code_LT01_6_count   0.51930    0.15545   3.341   0.0009 ***
## category_code_LT01_9_count   0.43399    0.23037   1.884   0.0602 .  
## category_code_LT01_12_count  0.04971    0.21195   0.235   0.8147    
## category_code_LT01_14_count  0.40184    0.33398   1.203   0.2295    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.412 on 491 degrees of freedom
## Multiple R-squared:  0.612,  Adjusted R-squared:  0.6072 
## F-statistic: 129.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 0.606279096697157 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0287 -0.8337  0.0087  0.9772  3.8259 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97510    0.08925 111.769  < 2e-16 ***
## category_code_LT01_2_count   0.86329    0.07623  11.324  < 2e-16 ***
## category_code_LT01_5_count   0.96471    0.06303  15.304  < 2e-16 ***
## category_code_LT01_6_count   0.49854    0.15536   3.209  0.00142 ** 
## category_code_LT01_9_count   0.45800    0.23000   1.991  0.04700 *  
## category_code_LT01_12_count  0.07483    0.21141   0.354  0.72354    
## category_code_LT01_15_count  0.39781    0.76413   0.521  0.60288    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.413 on 491 degrees of freedom
## Multiple R-squared:  0.611,  Adjusted R-squared:  0.6063 
## F-statistic: 128.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 0.606173468045057 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0282 -0.8345  0.0122  0.9727  3.8257 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97524    0.08926 111.752  < 2e-16 ***
## category_code_LT01_2_count   0.86435    0.07643  11.309  < 2e-16 ***
## category_code_LT01_5_count   0.96387    0.06307  15.283  < 2e-16 ***
## category_code_LT01_6_count   0.50913    0.15585   3.267  0.00116 ** 
## category_code_LT01_9_count   0.45270    0.23011   1.967  0.04971 *  
## category_code_LT01_12_count  0.07311    0.21139   0.346  0.72959    
## category_code_LT01_16_count  0.44802    1.20056   0.373  0.70918    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.413 on 491 degrees of freedom
## Multiple R-squared:  0.6109, Adjusted R-squared:  0.6062 
## F-statistic: 128.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 0.608143201868195 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0236 -0.8044  0.0335  0.9647  3.8230 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97797    0.08909 111.993  < 2e-16 ***
## category_code_LT01_2_count   0.84240    0.07620  11.055  < 2e-16 ***
## category_code_LT01_5_count   0.95330    0.06321  15.081  < 2e-16 ***
## category_code_LT01_6_count   0.52294    0.15414   3.393 0.000748 ***
## category_code_LT01_9_count   0.44812    0.23047   1.944 0.052417 .  
## category_code_LT01_13_count  0.27194    0.24700   1.101 0.271457    
## category_code_LT01_14_count  0.40346    0.33229   1.214 0.225268    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.41 on 491 degrees of freedom
## Multiple R-squared:  0.6129, Adjusted R-squared:  0.6081 
## F-statistic: 129.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 0.607234583244946 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0269 -0.8208  0.0019  0.9787  3.8267 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97427    0.08914 111.891  < 2e-16 ***
## category_code_LT01_2_count   0.85445    0.07556  11.308  < 2e-16 ***
## category_code_LT01_5_count   0.96336    0.06276  15.351  < 2e-16 ***
## category_code_LT01_6_count   0.50367    0.15415   3.267  0.00116 ** 
## category_code_LT01_9_count   0.47327    0.23008   2.057  0.04022 *  
## category_code_LT01_13_count  0.28456    0.24767   1.149  0.25114    
## category_code_LT01_15_count  0.44230    0.76428   0.579  0.56304    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.412 on 491 degrees of freedom
## Multiple R-squared:  0.612,  Adjusted R-squared:  0.6072 
## F-statistic: 129.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 0.607105687667046 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0264 -0.8216  0.0117  0.9726  3.8265 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97445    0.08916 111.872  < 2e-16 ***
## category_code_LT01_2_count   0.85566    0.07577  11.293  < 2e-16 ***
## category_code_LT01_5_count   0.96241    0.06279  15.326  < 2e-16 ***
## category_code_LT01_6_count   0.51532    0.15467   3.332 0.000928 ***
## category_code_LT01_9_count   0.46714    0.23017   2.030 0.042940 *  
## category_code_LT01_13_count  0.28056    0.24751   1.134 0.257543    
## category_code_LT01_16_count  0.50020    1.20010   0.417 0.677005    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.412 on 491 degrees of freedom
## Multiple R-squared:  0.6118, Adjusted R-squared:  0.6071 
## F-statistic:   129 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 0.607361663055302 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0271 -0.8193  0.0116  0.9599  3.8219 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97902    0.08918 111.899  < 2e-16 ***
## category_code_LT01_2_count   0.85059    0.07600  11.192  < 2e-16 ***
## category_code_LT01_5_count   0.95679    0.06321  15.136  < 2e-16 ***
## category_code_LT01_6_count   0.51921    0.15457   3.359 0.000843 ***
## category_code_LT01_9_count   0.43633    0.23039   1.894 0.058827 .  
## category_code_LT01_14_count  0.40466    0.33270   1.216 0.224455    
## category_code_LT01_15_count  0.36787    0.76315   0.482 0.629995    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.411 on 491 degrees of freedom
## Multiple R-squared:  0.6121, Adjusted R-squared:  0.6074 
## F-statistic: 129.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 0.607342910586322 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0265 -0.8190  0.0282  0.9559  3.8216 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97937    0.08919 111.894  < 2e-16 ***
## category_code_LT01_2_count   0.84947    0.07644  11.114  < 2e-16 ***
## category_code_LT01_5_count   0.95541    0.06325  15.104  < 2e-16 ***
## category_code_LT01_6_count   0.53111    0.15514   3.423  0.00067 ***
## category_code_LT01_9_count   0.42976    0.23051   1.864  0.06287 .  
## category_code_LT01_14_count  0.41938    0.33340   1.258  0.20903    
## category_code_LT01_16_count  0.54920    1.20162   0.457  0.64783    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.411 on 491 degrees of freedom
## Multiple R-squared:  0.6121, Adjusted R-squared:  0.6073 
## F-statistic: 129.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 0.606298676886995 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0300 -0.8245  0.0011  0.9779  3.8255 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97550    0.08925 111.773  < 2e-16 ***
## category_code_LT01_2_count   0.86422    0.07555  11.439  < 2e-16 ***
## category_code_LT01_5_count   0.96611    0.06278  15.388  < 2e-16 ***
## category_code_LT01_6_count   0.51071    0.15507   3.294  0.00106 ** 
## category_code_LT01_9_count   0.45541    0.23011   1.979  0.04837 *  
## category_code_LT01_15_count  0.40140    0.76432   0.525  0.59970    
## category_code_LT01_16_count  0.46465    1.20094   0.387  0.69899    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.413 on 491 degrees of freedom
## Multiple R-squared:  0.6111, Adjusted R-squared:  0.6063 
## F-statistic: 128.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.615910322719944 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0211 -0.7922  0.0168  0.9475  3.8953 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97031    0.09136 109.128  < 2e-16 ***
## category_code_LT01_2_count   0.68862    0.08963   7.683 8.53e-14 ***
## category_code_LT01_5_count   0.96073    0.06214  15.461  < 2e-16 ***
## category_code_LT01_6_count   0.40820    0.15652   2.608  0.00938 ** 
## category_code_LT01_10_count  0.09437    0.11449   0.824  0.41019    
## category_code_LT01_11_count  0.46599    0.11732   3.972 8.19e-05 ***
## category_code_LT01_12_count -0.13203    0.21490  -0.614  0.53924    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6205, Adjusted R-squared:  0.6159 
## F-statistic: 133.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.615982036251419 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0176 -0.8115  0.0468  0.9437  3.9147 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96993    0.09135 109.136  < 2e-16 ***
## category_code_LT01_2_count   0.68267    0.08982   7.600 1.51e-13 ***
## category_code_LT01_5_count   0.95619    0.06199  15.425  < 2e-16 ***
## category_code_LT01_6_count   0.40338    0.15614   2.583 0.010069 *  
## category_code_LT01_10_count  0.09054    0.11452   0.791 0.429564    
## category_code_LT01_11_count  0.44293    0.11433   3.874 0.000122 ***
## category_code_LT01_13_count  0.16782    0.24499   0.685 0.493663    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6206, Adjusted R-squared:  0.616 
## F-statistic: 133.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.616334749062532 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0214 -0.8131  0.0414  0.9288  3.8974 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97819    0.09171 108.803  < 2e-16 ***
## category_code_LT01_2_count   0.67637    0.09024   7.495 3.12e-13 ***
## category_code_LT01_5_count   0.94974    0.06248  15.200  < 2e-16 ***
## category_code_LT01_6_count   0.41936    0.15715   2.668 0.007873 ** 
## category_code_LT01_10_count  0.06690    0.11761   0.569 0.569747    
## category_code_LT01_11_count  0.44182    0.11418   3.870 0.000124 ***
## category_code_LT01_14_count  0.32416    0.33776   0.960 0.337671    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6163 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.615637545472649 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0192 -0.8154  0.0323  0.9383  3.9111 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97033    0.09141 109.068  < 2e-16 ***
## category_code_LT01_2_count   0.68611    0.08981   7.639 1.15e-13 ***
## category_code_LT01_5_count   0.95791    0.06198  15.455  < 2e-16 ***
## category_code_LT01_6_count   0.40053    0.15627   2.563 0.010673 *  
## category_code_LT01_10_count  0.09162    0.11482   0.798 0.425287    
## category_code_LT01_11_count  0.44778    0.11425   3.919 0.000101 ***
## category_code_LT01_15_count  0.12855    0.75822   0.170 0.865436    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6203, Adjusted R-squared:  0.6156 
## F-statistic: 133.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.615743655692378 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0190 -0.8139  0.0398  0.9393  3.9082 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97077    0.09140 109.088  < 2e-16 ***
## category_code_LT01_2_count   0.68234    0.09038   7.550 2.14e-13 ***
## category_code_LT01_5_count   0.95698    0.06200  15.436  < 2e-16 ***
## category_code_LT01_6_count   0.40798    0.15699   2.599  0.00964 ** 
## category_code_LT01_10_count  0.09062    0.11466   0.790  0.42969    
## category_code_LT01_11_count  0.44910    0.11402   3.939 9.38e-05 ***
## category_code_LT01_16_count  0.48112    1.18680   0.405  0.68537    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6204, Adjusted R-squared:  0.6157 
## F-statistic: 133.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 0.604315169253653 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0170 -0.8081 -0.0157  0.9750  3.8428 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95811    0.09268 107.448  < 2e-16 ***
## category_code_LT01_2_count   0.88379    0.07508  11.772  < 2e-16 ***
## category_code_LT01_5_count   0.97246    0.06302  15.431  < 2e-16 ***
## category_code_LT01_6_count   0.50016    0.15717   3.182  0.00155 ** 
## category_code_LT01_10_count  0.10097    0.11624   0.869  0.38547    
## category_code_LT01_12_count  0.06334    0.21205   0.299  0.76528    
## category_code_LT01_13_count  0.23873    0.24806   0.962  0.33634    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6091, Adjusted R-squared:  0.6043 
## F-statistic: 127.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 0.604675879531511 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0222 -0.8349 -0.0030  0.9555  3.8326 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96838    0.09306 107.120  < 2e-16 ***
## category_code_LT01_2_count   0.87773    0.07557  11.614  < 2e-16 ***
## category_code_LT01_5_count   0.96514    0.06349  15.202  < 2e-16 ***
## category_code_LT01_6_count   0.52081    0.15820   3.292  0.00107 ** 
## category_code_LT01_10_count  0.07226    0.11938   0.605  0.54527    
## category_code_LT01_12_count  0.04820    0.21264   0.227  0.82076    
## category_code_LT01_14_count  0.40266    0.34339   1.173  0.24152    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 491 degrees of freedom
## Multiple R-squared:  0.6094, Adjusted R-squared:  0.6047 
## F-statistic: 127.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 0.603705722247442 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0196 -0.8073 -0.0228  0.9711  3.8421 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95887    0.09277 107.345  < 2e-16 ***
## category_code_LT01_2_count   0.88975    0.07504  11.858  < 2e-16 ***
## category_code_LT01_5_count   0.97507    0.06302  15.473  < 2e-16 ***
## category_code_LT01_6_count   0.49580    0.15746   3.149  0.00174 ** 
## category_code_LT01_10_count  0.10107    0.11660   0.867  0.38647    
## category_code_LT01_12_count  0.07168    0.21217   0.338  0.73564    
## category_code_LT01_15_count  0.31658    0.76867   0.412  0.68062    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 491 degrees of freedom
## Multiple R-squared:  0.6085, Adjusted R-squared:  0.6037 
## F-statistic: 127.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 0.603692401385887 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0188 -0.8267 -0.0211  0.9699  3.8422 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95875    0.09277 107.347  < 2e-16 ***
## category_code_LT01_2_count   0.88902    0.07537  11.795  < 2e-16 ***
## category_code_LT01_5_count   0.97411    0.06305  15.450  < 2e-16 ***
## category_code_LT01_6_count   0.50523    0.15813   3.195  0.00149 ** 
## category_code_LT01_10_count  0.10231    0.11643   0.879  0.37997    
## category_code_LT01_12_count  0.07041    0.21212   0.332  0.74009    
## category_code_LT01_16_count  0.47164    1.20532   0.391  0.69574    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 491 degrees of freedom
## Multiple R-squared:  0.6085, Adjusted R-squared:  0.6037 
## F-statistic: 127.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 0.605391382122588 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0215 -0.8292 -0.0055  0.9569  3.8324 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96860    0.09297 107.221  < 2e-16 ***
## category_code_LT01_2_count   0.87056    0.07494  11.617  < 2e-16 ***
## category_code_LT01_5_count   0.96370    0.06327  15.230  < 2e-16 ***
## category_code_LT01_6_count   0.52582    0.15696   3.350  0.00087 ***
## category_code_LT01_10_count  0.06859    0.11933   0.575  0.56571    
## category_code_LT01_13_count  0.24029    0.24761   0.970  0.33230    
## category_code_LT01_14_count  0.40855    0.34182   1.195  0.23257    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 491 degrees of freedom
## Multiple R-squared:  0.6102, Adjusted R-squared:  0.6054 
## F-statistic: 128.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 0.604415505827977 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0193 -0.8013 -0.0237  0.9851  3.8419 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95903    0.09269 107.443  < 2e-16 ***
## category_code_LT01_2_count   0.88375    0.07420  11.911  < 2e-16 ***
## category_code_LT01_5_count   0.97439    0.06274  15.530  < 2e-16 ***
## category_code_LT01_6_count   0.50208    0.15636   3.211  0.00141 ** 
## category_code_LT01_10_count  0.09764    0.11654   0.838  0.40257    
## category_code_LT01_13_count  0.24776    0.24835   0.998  0.31894    
## category_code_LT01_15_count  0.35561    0.76910   0.462  0.64401    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6092, Adjusted R-squared:  0.6044 
## F-statistic: 127.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 0.604393789046628 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0184 -0.8068 -0.0267  0.9828  3.8421 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95888    0.09269 107.444  < 2e-16 ***
## category_code_LT01_2_count   0.88300    0.07456  11.843  < 2e-16 ***
## category_code_LT01_5_count   0.97330    0.06278  15.504  < 2e-16 ***
## category_code_LT01_6_count   0.51243    0.15708   3.262  0.00118 ** 
## category_code_LT01_10_count  0.09909    0.11637   0.852  0.39491    
## category_code_LT01_13_count  0.24579    0.24817   0.990  0.32247    
## category_code_LT01_16_count  0.52102    1.20540   0.432  0.66576    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6092, Adjusted R-squared:  0.6044 
## F-statistic: 127.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 0.604760842939598 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0242 -0.8165  0.0007  0.9529  3.8316 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96931    0.09307 107.117  < 2e-16 ***
## category_code_LT01_2_count   0.87734    0.07478  11.732  < 2e-16 ***
## category_code_LT01_5_count   0.96656    0.06327  15.276  < 2e-16 ***
## category_code_LT01_6_count   0.52224    0.15724   3.321 0.000963 ***
## category_code_LT01_10_count  0.06898    0.11967   0.576 0.564592    
## category_code_LT01_14_count  0.40840    0.34210   1.194 0.233127    
## category_code_LT01_15_count  0.30404    0.76745   0.396 0.692152    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 491 degrees of freedom
## Multiple R-squared:  0.6095, Adjusted R-squared:  0.6048 
## F-statistic: 127.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 0.604825489172615 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0236 -0.8317 -0.0003  0.9539  3.8312 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96978    0.09308 107.114  < 2e-16 ***
## category_code_LT01_2_count   0.87461    0.07535  11.607  < 2e-16 ***
## category_code_LT01_5_count   0.96501    0.06332  15.240  < 2e-16 ***
## category_code_LT01_6_count   0.53377    0.15808   3.376 0.000792 ***
## category_code_LT01_10_count  0.06830    0.11965   0.571 0.568387    
## category_code_LT01_14_count  0.42288    0.34319   1.232 0.218460    
## category_code_LT01_16_count  0.58821    1.20750   0.487 0.626382    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 491 degrees of freedom
## Multiple R-squared:  0.6096, Adjusted R-squared:  0.6048 
## F-statistic: 127.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 0.603744833624018 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0212 -0.8075 -0.0240  0.9762  3.8414 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.95958    0.09279 107.334  < 2e-16 ***
## category_code_LT01_2_count   0.89014    0.07439  11.967  < 2e-16 ***
## category_code_LT01_5_count   0.97629    0.06277  15.554  < 2e-16 ***
## category_code_LT01_6_count   0.50820    0.15733   3.230  0.00132 ** 
## category_code_LT01_10_count  0.09953    0.11673   0.853  0.39428    
## category_code_LT01_15_count  0.32181    0.76893   0.419  0.67575    
## category_code_LT01_16_count  0.48631    1.20600   0.403  0.68695    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.418 on 491 degrees of freedom
## Multiple R-squared:  0.6085, Adjusted R-squared:  0.6037 
## F-statistic: 127.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.615783019485177 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0392 -0.7790  0.0278  0.9446  3.8440 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98948    0.08817 113.297  < 2e-16 ***
## category_code_LT01_2_count   0.68992    0.08959   7.701 7.52e-14 ***
## category_code_LT01_5_count   0.95919    0.06219  15.423  < 2e-16 ***
## category_code_LT01_6_count   0.42945    0.15473   2.775  0.00572 ** 
## category_code_LT01_11_count  0.46205    0.11762   3.928 9.78e-05 ***
## category_code_LT01_12_count -0.13080    0.21492  -0.609  0.54308    
## category_code_LT01_13_count  0.17604    0.24495   0.719  0.47268    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6204, Adjusted R-squared:  0.6158 
## F-statistic: 133.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.616449096125389 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0379 -0.7924  0.0318  0.9515  3.8407 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99339    0.08813 113.388  < 2e-16 ***
## category_code_LT01_2_count   0.68017    0.09013   7.547 2.18e-13 ***
## category_code_LT01_5_count   0.95163    0.06259  15.204  < 2e-16 ***
## category_code_LT01_6_count   0.44364    0.15517   2.859  0.00443 ** 
## category_code_LT01_11_count  0.46127    0.11736   3.931 9.69e-05 ***
## category_code_LT01_12_count -0.14762    0.21532  -0.686  0.49330    
## category_code_LT01_14_count  0.38562    0.32945   1.171  0.24237    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.615412172231939 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0411 -0.7949  0.0254  0.9404  3.8405 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99012    0.08821 113.255  < 2e-16 ***
## category_code_LT01_2_count   0.69338    0.08961   7.737 5.82e-14 ***
## category_code_LT01_5_count   0.96094    0.06218  15.453  < 2e-16 ***
## category_code_LT01_6_count   0.42630    0.15497   2.751  0.00617 ** 
## category_code_LT01_11_count  0.46649    0.11766   3.965 8.44e-05 ***
## category_code_LT01_12_count -0.12704    0.21516  -0.590  0.55517    
## category_code_LT01_15_count  0.15614    0.75693   0.206  0.83665    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.397 on 491 degrees of freedom
## Multiple R-squared:  0.6201, Adjusted R-squared:  0.6154 
## F-statistic: 133.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.615532067462692 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0406 -0.7799  0.0262  0.9422  3.8375 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99038    0.08820 113.273  < 2e-16 ***
## category_code_LT01_2_count   0.68934    0.09019   7.643 1.12e-13 ***
## category_code_LT01_5_count   0.95993    0.06220  15.432  < 2e-16 ***
## category_code_LT01_6_count   0.43438    0.15547   2.794  0.00541 ** 
## category_code_LT01_11_count  0.46816    0.11735   3.990 7.63e-05 ***
## category_code_LT01_12_count -0.12793    0.21498  -0.595  0.55206    
## category_code_LT01_16_count  0.52444    1.18554   0.442  0.65842    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.397 on 491 degrees of freedom
## Multiple R-squared:  0.6202, Adjusted R-squared:  0.6155 
## F-statistic: 133.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616470972520284 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0333 -0.8042  0.0415  0.9368  3.8641 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99197    0.08813 113.379  < 2e-16 ***
## category_code_LT01_2_count   0.67434    0.09035   7.464 3.86e-13 ***
## category_code_LT01_5_count   0.94713    0.06249  15.157  < 2e-16 ***
## category_code_LT01_6_count   0.43653    0.15468   2.822 0.004964 ** 
## category_code_LT01_11_count  0.43635    0.11449   3.811 0.000156 ***
## category_code_LT01_13_count  0.17270    0.24471   0.706 0.480692    
## category_code_LT01_14_count  0.36755    0.32851   1.119 0.263761    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6165 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.615551508753051 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0368 -0.8257  0.0312  0.9379  3.8639 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98893    0.08819 113.263  < 2e-16 ***
## category_code_LT01_2_count   0.68655    0.08983   7.643 1.13e-13 ***
## category_code_LT01_5_count   0.95646    0.06203  15.420  < 2e-16 ***
## category_code_LT01_6_count   0.42055    0.15451   2.722 0.006722 ** 
## category_code_LT01_11_count  0.44310    0.11462   3.866 0.000126 ***
## category_code_LT01_13_count  0.17814    0.24547   0.726 0.468346    
## category_code_LT01_15_count  0.20678    0.75768   0.273 0.785030    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6202, Adjusted R-squared:  0.6156 
## F-statistic: 133.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.615672163925087 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0362 -0.8135  0.0429  0.9386  3.8596 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98919    0.08818 113.281  < 2e-16 ***
## category_code_LT01_2_count   0.68246    0.09042   7.548 2.17e-13 ***
## category_code_LT01_5_count   0.95529    0.06205  15.396  < 2e-16 ***
## category_code_LT01_6_count   0.42960    0.15505   2.771 0.005806 ** 
## category_code_LT01_11_count  0.44511    0.11434   3.893 0.000113 ***
## category_code_LT01_13_count  0.17905    0.24519   0.730 0.465596    
## category_code_LT01_16_count  0.56729    1.18637   0.478 0.632738    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.396 on 491 degrees of freedom
## Multiple R-squared:  0.6203, Adjusted R-squared:  0.6157 
## F-statistic: 133.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616115323179902 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0352 -0.8077  0.0291  0.9402  3.8604 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99261    0.08817 113.339  < 2e-16 ***
## category_code_LT01_2_count   0.67776    0.09035   7.502 2.98e-13 ***
## category_code_LT01_5_count   0.94894    0.06248  15.187  < 2e-16 ***
## category_code_LT01_6_count   0.43360    0.15491   2.799 0.005327 ** 
## category_code_LT01_11_count  0.44115    0.11442   3.855 0.000131 ***
## category_code_LT01_14_count  0.36732    0.32873   1.117 0.264366    
## category_code_LT01_15_count  0.15620    0.75584   0.207 0.836367    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.6161 
## F-statistic: 133.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.616296085246265 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0346 -0.8055  0.0365  0.9429  3.8580 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99302    0.08815 113.366  < 2e-16 ***
## category_code_LT01_2_count   0.67223    0.09105   7.383 6.68e-13 ***
## category_code_LT01_5_count   0.94743    0.06251  15.157  < 2e-16 ***
## category_code_LT01_6_count   0.44334    0.15550   2.851 0.004541 ** 
## category_code_LT01_11_count  0.44241    0.11418   3.875 0.000121 ***
## category_code_LT01_14_count  0.38014    0.32931   1.154 0.248923    
## category_code_LT01_16_count  0.62135    1.18694   0.523 0.600874    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.6163 
## F-statistic:   134 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.615301212194342 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0382 -0.8270  0.0322  0.9364  3.8563 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98986    0.08822 113.239  < 2e-16 ***
## category_code_LT01_2_count   0.68609    0.09042   7.588 1.65e-13 ***
## category_code_LT01_5_count   0.95724    0.06204  15.430  < 2e-16 ***
## category_code_LT01_6_count   0.42602    0.15524   2.744  0.00629 ** 
## category_code_LT01_11_count  0.44987    0.11427   3.937 9.45e-05 ***
## category_code_LT01_15_count  0.18427    0.75690   0.243  0.80775    
## category_code_LT01_16_count  0.53968    1.18648   0.455  0.64941    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.397 on 491 degrees of freedom
## Multiple R-squared:  0.6199, Adjusted R-squared:  0.6153 
## F-statistic: 133.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.605157735315112 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0347 -0.8223  0.0014  0.9478  3.8177 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98322    0.08939 111.679  < 2e-16 ***
## category_code_LT01_2_count   0.87068    0.07606  11.448  < 2e-16 ***
## category_code_LT01_5_count   0.96164    0.06347  15.151  < 2e-16 ***
## category_code_LT01_6_count   0.53842    0.15555   3.462 0.000584 ***
## category_code_LT01_12_count  0.04232    0.21260   0.199 0.842319    
## category_code_LT01_13_count  0.24342    0.24767   0.983 0.326160    
## category_code_LT01_14_count  0.44838    0.33385   1.343 0.179864    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 491 degrees of freedom
## Multiple R-squared:  0.6099, Adjusted R-squared:  0.6052 
## F-statistic:   128 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.603937853567319 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0384 -0.8271 -0.0296  0.9734  3.8216 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97935    0.08948 111.525  < 2e-16 ***
## category_code_LT01_2_count   0.88528    0.07542  11.738  < 2e-16 ***
## category_code_LT01_5_count   0.97268    0.06305  15.427  < 2e-16 ***
## category_code_LT01_6_count   0.51672    0.15556   3.322 0.000961 ***
## category_code_LT01_12_count  0.06999    0.21213   0.330 0.741594    
## category_code_LT01_13_count  0.25329    0.24843   1.020 0.308426    
## category_code_LT01_15_count  0.41044    0.76742   0.535 0.593013    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6087, Adjusted R-squared:  0.6039 
## F-statistic: 127.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.603893576912533 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0378 -0.8429 -0.0342  0.9736  3.8214 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97951    0.08949 111.519  < 2e-16 ***
## category_code_LT01_2_count   0.88489    0.07574  11.683  < 2e-16 ***
## category_code_LT01_5_count   0.97151    0.06309  15.399  < 2e-16 ***
## category_code_LT01_6_count   0.52888    0.15602   3.390 0.000756 ***
## category_code_LT01_12_count  0.06843    0.21211   0.323 0.747109    
## category_code_LT01_13_count  0.25099    0.24828   1.011 0.312553    
## category_code_LT01_16_count  0.57904    1.20444   0.481 0.630907    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6087, Adjusted R-squared:  0.6039 
## F-statistic: 127.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.604539676688752 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0373 -0.8231 -0.0046  0.9484  3.8169 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98401    0.08946 111.604  < 2e-16 ***
## category_code_LT01_2_count   0.87660    0.07603  11.530  < 2e-16 ***
## category_code_LT01_5_count   0.96435    0.06348  15.192  < 2e-16 ***
## category_code_LT01_6_count   0.53374    0.15596   3.422 0.000673 ***
## category_code_LT01_12_count  0.05100    0.21273   0.240 0.810620    
## category_code_LT01_14_count  0.44694    0.33421   1.337 0.181745    
## category_code_LT01_15_count  0.34006    0.76592   0.444 0.657243    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 491 degrees of freedom
## Multiple R-squared:  0.6093, Adjusted R-squared:  0.6045 
## F-statistic: 127.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.604606024178482 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0366 -0.8316 -0.0045  0.9425  3.8166 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98436    0.08946 111.612  < 2e-16 ***
## category_code_LT01_2_count   0.87387    0.07657  11.413  < 2e-16 ***
## category_code_LT01_5_count   0.96272    0.06352  15.156  < 2e-16 ***
## category_code_LT01_6_count   0.54636    0.15646   3.492 0.000523 ***
## category_code_LT01_12_count  0.04901    0.21265   0.230 0.817823    
## category_code_LT01_14_count  0.46252    0.33480   1.381 0.167757    
## category_code_LT01_16_count  0.63706    1.20489   0.529 0.597233    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 491 degrees of freedom
## Multiple R-squared:  0.6094, Adjusted R-squared:  0.6046 
## F-statistic: 127.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.603265698286625 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0406 -0.8285 -0.0382  0.9649  3.8206 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98033    0.08956 111.442  < 2e-16 ***
## category_code_LT01_2_count   0.89088    0.07572  11.765  < 2e-16 ***
## category_code_LT01_5_count   0.97434    0.06308  15.445  < 2e-16 ***
## category_code_LT01_6_count   0.52336    0.15638   3.347  0.00088 ***
## category_code_LT01_12_count  0.07743    0.21222   0.365  0.71539    
## category_code_LT01_15_count  0.37845    0.76730   0.493  0.62207    
## category_code_LT01_16_count  0.54681    1.20495   0.454  0.65017    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.419 on 491 degrees of freedom
## Multiple R-squared:  0.6081, Adjusted R-squared:  0.6033 
## F-statistic:   127 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.605323147583127 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0358 -0.8102  0.0061  0.9479  3.8175 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98343    0.08937 111.707  < 2e-16 ***
## category_code_LT01_2_count   0.86847    0.07545  11.511  < 2e-16 ***
## category_code_LT01_5_count   0.96295    0.06326  15.223  < 2e-16 ***
## category_code_LT01_6_count   0.53764    0.15464   3.477 0.000553 ***
## category_code_LT01_13_count  0.25186    0.24789   1.016 0.310125    
## category_code_LT01_14_count  0.45019    0.33256   1.354 0.176441    
## category_code_LT01_15_count  0.37955    0.76616   0.495 0.620545    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 491 degrees of freedom
## Multiple R-squared:  0.6101, Adjusted R-squared:  0.6053 
## F-statistic:   128 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.605387823131821 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0349 -0.8220  0.0039  0.9456  3.8172 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98380    0.08937 111.716  < 2e-16 ***
## category_code_LT01_2_count   0.86557    0.07603  11.385  < 2e-16 ***
## category_code_LT01_5_count   0.96114    0.06330  15.183  < 2e-16 ***
## category_code_LT01_6_count   0.55122    0.15517   3.552 0.000419 ***
## category_code_LT01_13_count  0.25090    0.24770   1.013 0.311603    
## category_code_LT01_14_count  0.46685    0.33315   1.401 0.161748    
## category_code_LT01_16_count  0.68780    1.20476   0.571 0.568329    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.415 on 491 degrees of freedom
## Multiple R-squared:  0.6102, Adjusted R-squared:  0.6054 
## F-statistic: 128.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.604049603382353 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0395 -0.8184 -0.0367  0.9728  3.8212 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97977    0.08947 111.544  < 2e-16 ***
## category_code_LT01_2_count   0.88389    0.07495  11.792  < 2e-16 ***
## category_code_LT01_5_count   0.97358    0.06280  15.502  < 2e-16 ***
## category_code_LT01_6_count   0.53003    0.15521   3.415 0.000691 ***
## category_code_LT01_13_count  0.26130    0.24852   1.051 0.293589    
## category_code_LT01_15_count  0.41877    0.76763   0.546 0.585629    
## category_code_LT01_16_count  0.59939    1.20491   0.497 0.619092    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.417 on 491 degrees of freedom
## Multiple R-squared:  0.6088, Adjusted R-squared:  0.604 
## F-statistic: 127.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.604729993589637 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0378 -0.8159 -0.0041  0.9410  3.8163 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98462    0.08944 111.635  < 2e-16 ***
## category_code_LT01_2_count   0.87267    0.07587  11.502  < 2e-16 ***
## category_code_LT01_5_count   0.96422    0.06330  15.232  < 2e-16 ***
## category_code_LT01_6_count   0.54675    0.15554   3.515  0.00048 ***
## category_code_LT01_14_count  0.46601    0.33350   1.397  0.16295    
## category_code_LT01_15_count  0.34856    0.76589   0.455  0.64923    
## category_code_LT01_16_count  0.65343    1.20528   0.542  0.58797    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.416 on 491 degrees of freedom
## Multiple R-squared:  0.6095, Adjusted R-squared:  0.6047 
## F-statistic: 127.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 0.611368194346012 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0330 -0.7743  0.0155  0.9430  3.8296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97138    0.09188 108.531  < 2e-16 ***
## category_code_LT01_2_count   0.86608    0.07127  12.153  < 2e-16 ***
## category_code_LT01_5_count   0.97638    0.06273  15.565  < 2e-16 ***
## category_code_LT01_7_count   0.62017    0.15347   4.041 6.18e-05 ***
## category_code_LT01_8_count  -0.13716    0.27820  -0.493    0.622    
## category_code_LT01_9_count   0.37606    0.23109   1.627    0.104    
## category_code_LT01_10_count  0.10295    0.11483   0.897    0.370    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6161, Adjusted R-squared:  0.6114 
## F-statistic: 131.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 0.619206895489007 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0502 -0.7849  0.0046  0.9102  3.8019 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99903    0.08766 114.066  < 2e-16 ***
## category_code_LT01_2_count   0.70292    0.08713   8.067 5.56e-15 ***
## category_code_LT01_5_count   0.96131    0.06227  15.439  < 2e-16 ***
## category_code_LT01_7_count   0.48107    0.15809   3.043  0.00247 ** 
## category_code_LT01_8_count  -0.11137    0.27540  -0.404  0.68611    
## category_code_LT01_9_count   0.36158    0.22756   1.589  0.11273    
## category_code_LT01_11_count  0.38675    0.11699   3.306  0.00102 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6238, Adjusted R-squared:  0.6192 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 0.611082469242403 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0518 -0.7824 -0.0029  0.9530  3.8082 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99280    0.08858 112.814  < 2e-16 ***
## category_code_LT01_2_count   0.86287    0.07298  11.824  < 2e-16 ***
## category_code_LT01_5_count   0.97257    0.06307  15.421  < 2e-16 ***
## category_code_LT01_7_count   0.62892    0.15310   4.108 4.68e-05 ***
## category_code_LT01_8_count  -0.13976    0.27846  -0.502   0.6160    
## category_code_LT01_9_count   0.39837    0.22969   1.734   0.0835 .  
## category_code_LT01_12_count  0.13895    0.20889   0.665   0.5062    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6158, Adjusted R-squared:  0.6111 
## F-statistic: 131.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 0.610953989380001 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0538 -0.7917 -0.0005  0.9650  3.8081 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99286    0.08859 112.795  < 2e-16 ***
## category_code_LT01_2_count   0.87097    0.07103  12.262  < 2e-16 ***
## category_code_LT01_5_count   0.97529    0.06282  15.525  < 2e-16 ***
## category_code_LT01_7_count   0.61885    0.15472   4.000 7.32e-05 ***
## category_code_LT01_8_count  -0.12392    0.27877  -0.445    0.657    
## category_code_LT01_9_count   0.40801    0.23028   1.772    0.077 .  
## category_code_LT01_13_count  0.13182    0.24904   0.529    0.597    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6157, Adjusted R-squared:  0.611 
## F-statistic: 131.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 0.611041759867098 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0546 -0.7852  0.0038  0.9500  3.8053 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99563    0.08865 112.752   <2e-16 ***
## category_code_LT01_2_count   0.86892    0.07128  12.190   <2e-16 ***
## category_code_LT01_5_count   0.97245    0.06313  15.404   <2e-16 ***
## category_code_LT01_7_count   0.62216    0.15369   4.048    6e-05 ***
## category_code_LT01_8_count  -0.13471    0.27829  -0.484   0.6285    
## category_code_LT01_9_count   0.39048    0.23016   1.697   0.0904 .  
## category_code_LT01_14_count  0.20726    0.33144   0.625   0.5320    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6157, Adjusted R-squared:  0.611 
## F-statistic: 131.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 0.611185037566631 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0553 -0.7829 -0.0086  0.9600  3.8076 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99333    0.08856 112.841  < 2e-16 ***
## category_code_LT01_2_count   0.86599    0.07160  12.095  < 2e-16 ***
## category_code_LT01_5_count   0.97678    0.06274  15.569  < 2e-16 ***
## category_code_LT01_7_count   0.63183    0.15306   4.128  4.3e-05 ***
## category_code_LT01_8_count  -0.13565    0.27824  -0.488   0.6261    
## category_code_LT01_9_count   0.40238    0.22969   1.752   0.0804 .  
## category_code_LT01_15_count  0.57333    0.75799   0.756   0.4498    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6159, Adjusted R-squared:  0.6112 
## F-statistic: 131.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 0.610754205012402 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0555 -0.7908 -0.0064  0.9598  3.8073 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99361    0.08862 112.767  < 2e-16 ***
## category_code_LT01_2_count   0.87382    0.07112  12.286  < 2e-16 ***
## category_code_LT01_5_count   0.97668    0.06278  15.558  < 2e-16 ***
## category_code_LT01_7_count   0.63136    0.15320   4.121 4.42e-05 ***
## category_code_LT01_8_count  -0.13486    0.27872  -0.484   0.6287    
## category_code_LT01_9_count   0.39846    0.22988   1.733   0.0837 .  
## category_code_LT01_16_count  0.19910    1.18947   0.167   0.8671    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6155, Adjusted R-squared:  0.6108 
## F-statistic:   131 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 0.61801628036261 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0346 -0.7661  0.0146  0.9327  3.8220 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97897    0.09112 109.519  < 2e-16 ***
## category_code_LT01_2_count   0.71276    0.08696   8.197 2.17e-15 ***
## category_code_LT01_5_count   0.96771    0.06220  15.557  < 2e-16 ***
## category_code_LT01_7_count   0.49186    0.15814   3.110 0.001978 ** 
## category_code_LT01_8_count  -0.10275    0.27575  -0.373 0.709575    
## category_code_LT01_10_count  0.11238    0.11316   0.993 0.321137    
## category_code_LT01_11_count  0.39253    0.11708   3.353 0.000862 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 0.609591888515459 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0354 -0.7782 -0.0058  0.9361  3.8298 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97120    0.09209 108.282  < 2e-16 ***
## category_code_LT01_2_count   0.87742    0.07238  12.123  < 2e-16 ***
## category_code_LT01_5_count   0.98008    0.06301  15.554  < 2e-16 ***
## category_code_LT01_7_count   0.64370    0.15307   4.205  3.1e-05 ***
## category_code_LT01_8_count  -0.13014    0.27891  -0.467    0.641    
## category_code_LT01_10_count  0.12121    0.11444   1.059    0.290    
## category_code_LT01_12_count  0.13283    0.20945   0.634    0.526    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6096 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 0.609387819105603 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0374 -0.7729  0.0080  0.9316  3.8299 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97105    0.09211 108.252  < 2e-16 ***
## category_code_LT01_2_count   0.88647    0.07036  12.599  < 2e-16 ***
## category_code_LT01_5_count   0.98317    0.06275  15.667  < 2e-16 ***
## category_code_LT01_7_count   0.63716    0.15450   4.124 4.37e-05 ***
## category_code_LT01_8_count  -0.11683    0.27929  -0.418    0.676    
## category_code_LT01_10_count  0.12312    0.11441   1.076    0.282    
## category_code_LT01_13_count  0.09497    0.24901   0.381    0.703    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.6094 
## F-statistic: 130.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 0.609482971294254 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0401 -0.7851  0.0076  0.9259  3.8253 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97569    0.09252 107.819  < 2e-16 ***
## category_code_LT01_2_count   0.88452    0.07058  12.533  < 2e-16 ***
## category_code_LT01_5_count   0.98042    0.06311  15.536  < 2e-16 ***
## category_code_LT01_7_count   0.63889    0.15355   4.161 3.74e-05 ***
## category_code_LT01_8_count  -0.12479    0.27875  -0.448    0.655    
## category_code_LT01_10_count  0.11142    0.11700   0.952    0.341    
## category_code_LT01_14_count  0.17459    0.33908   0.515    0.607    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6095 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 0.609595038406819 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0395 -0.7734 -0.0055  0.9266  3.8285 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97246    0.09211 108.269  < 2e-16 ***
## category_code_LT01_2_count   0.88200    0.07089  12.443  < 2e-16 ***
## category_code_LT01_5_count   0.98422    0.06269  15.700  < 2e-16 ***
## category_code_LT01_7_count   0.64700    0.15308   4.227 2.83e-05 ***
## category_code_LT01_8_count  -0.12554    0.27872  -0.450    0.653    
## category_code_LT01_10_count  0.11797    0.11476   1.028    0.304    
## category_code_LT01_15_count  0.48572    0.76216   0.637    0.524    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6096 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 0.609297008802238 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0385 -0.7875 -0.0016  0.9268  3.8294 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97153    0.09215 108.213  < 2e-16 ***
## category_code_LT01_2_count   0.88751    0.07059  12.573  < 2e-16 ***
## category_code_LT01_5_count   0.98399    0.06272  15.689  < 2e-16 ***
## category_code_LT01_7_count   0.64585    0.15316   4.217 2.95e-05 ***
## category_code_LT01_8_count  -0.12581    0.27916  -0.451    0.652    
## category_code_LT01_10_count  0.12340    0.11447   1.078    0.282    
## category_code_LT01_16_count  0.21087    1.19201   0.177    0.860    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.614,  Adjusted R-squared:  0.6093 
## F-statistic: 130.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 0.617278723275712 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0605 -0.7515  0.0125  0.9191  3.7974 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00358    0.08785 113.871  < 2e-16 ***
## category_code_LT01_2_count   0.72392    0.08659   8.360  6.5e-16 ***
## category_code_LT01_5_count   0.96955    0.06248  15.519  < 2e-16 ***
## category_code_LT01_7_count   0.50192    0.15812   3.174 0.001597 ** 
## category_code_LT01_8_count  -0.09398    0.27624  -0.340 0.733849    
## category_code_LT01_11_count  0.40225    0.12125   3.318 0.000976 ***
## category_code_LT01_12_count -0.04191    0.21448  -0.195 0.845173    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 0.617310750463326 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0589 -0.7670  0.0143  0.9176  3.7979 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00309    0.08784 113.878  < 2e-16 ***
## category_code_LT01_2_count   0.72150    0.08658   8.334 7.92e-16 ***
## category_code_LT01_5_count   0.96789    0.06230  15.537  < 2e-16 ***
## category_code_LT01_7_count   0.49837    0.15899   3.135 0.001824 ** 
## category_code_LT01_8_count  -0.09184    0.27642  -0.332 0.739845    
## category_code_LT01_11_count  0.39487    0.11722   3.369 0.000815 ***
## category_code_LT01_13_count  0.06942    0.24658   0.282 0.778408    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 0.61756679621365 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0586 -0.7654  0.0068  0.9140  3.7955 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00547    0.08787 113.866  < 2e-16 ***
## category_code_LT01_2_count   0.71686    0.08692   8.247  1.5e-15 ***
## category_code_LT01_5_count   0.96406    0.06263  15.394  < 2e-16 ***
## category_code_LT01_7_count   0.49538    0.15832   3.129 0.001859 ** 
## category_code_LT01_8_count  -0.09918    0.27587  -0.360 0.719365    
## category_code_LT01_11_count  0.39388    0.11715   3.362 0.000833 ***
## category_code_LT01_14_count  0.20961    0.32814   0.639 0.523256    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6176 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 0.61741951952953 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0596 -0.7508 -0.0078  0.9210  3.7977 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00326    0.08782 113.902  < 2e-16 ***
## category_code_LT01_2_count   0.71927    0.08677   8.289  1.1e-15 ***
## category_code_LT01_5_count   0.96875    0.06225  15.563  < 2e-16 ***
## category_code_LT01_7_count   0.50633    0.15790   3.207 0.001431 ** 
## category_code_LT01_8_count  -0.09856    0.27592  -0.357 0.721101    
## category_code_LT01_11_count  0.39178    0.11749   3.335 0.000918 ***
## category_code_LT01_15_count  0.35283    0.75416   0.468 0.640098    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 0.617300638586002 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0597 -0.7509  0.0135  0.9214  3.7973 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00367    0.08785 113.875  < 2e-16 ***
## category_code_LT01_2_count   0.72040    0.08698   8.282 1.16e-15 ***
## category_code_LT01_5_count   0.96833    0.06226  15.553  < 2e-16 ***
## category_code_LT01_7_count   0.50457    0.15786   3.196  0.00148 ** 
## category_code_LT01_8_count  -0.10010    0.27629  -0.362  0.71728    
## category_code_LT01_11_count  0.39648    0.11714   3.385  0.00077 ***
## category_code_LT01_16_count  0.30357    1.17902   0.257  0.79692    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 0.608818101467303 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0612 -0.7866 -0.0218  0.9387  3.8039 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99709    0.08880 112.581  < 2e-16 ***
## category_code_LT01_2_count   0.88682    0.07187  12.339  < 2e-16 ***
## category_code_LT01_5_count   0.97999    0.06311  15.529  < 2e-16 ***
## category_code_LT01_7_count   0.64984    0.15407   4.218 2.94e-05 ***
## category_code_LT01_8_count  -0.11739    0.27966  -0.420    0.675    
## category_code_LT01_12_count  0.13924    0.20959   0.664    0.507    
## category_code_LT01_13_count  0.09601    0.24924   0.385    0.700    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6135, Adjusted R-squared:  0.6088 
## F-statistic: 129.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 0.609069183626486 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0614 -0.7923 -0.0157  0.9156  3.8012 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99978    0.08884 112.564  < 2e-16 ***
## category_code_LT01_2_count   0.88270    0.07221  12.224  < 2e-16 ***
## category_code_LT01_5_count   0.97627    0.06341  15.397  < 2e-16 ***
## category_code_LT01_7_count   0.64809    0.15326   4.229  2.8e-05 ***
## category_code_LT01_8_count  -0.12624    0.27905  -0.452    0.651    
## category_code_LT01_12_count  0.13056    0.21007   0.622    0.535    
## category_code_LT01_14_count  0.22655    0.33264   0.681    0.496    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6138, Adjusted R-squared:  0.6091 
## F-statistic: 130.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 0.609131844996843 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0621 -0.7869 -0.0254  0.9302  3.8036 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99736    0.08876 112.634  < 2e-16 ***
## category_code_LT01_2_count   0.88021    0.07261  12.123  < 2e-16 ***
## category_code_LT01_5_count   0.98086    0.06304  15.559  < 2e-16 ***
## category_code_LT01_7_count   0.65928    0.15257   4.321 1.88e-05 ***
## category_code_LT01_8_count  -0.12710    0.27904  -0.455    0.649    
## category_code_LT01_12_count  0.14415    0.20943   0.688    0.492    
## category_code_LT01_15_count  0.55983    0.75998   0.737    0.462    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6139, Adjusted R-squared:  0.6091 
## F-statistic: 130.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 0.608742323065805 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0623 -0.7872 -0.0282  0.9385  3.8033 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99768    0.08881 112.569  < 2e-16 ***
## category_code_LT01_2_count   0.88709    0.07223  12.282  < 2e-16 ***
## category_code_LT01_5_count   0.98067    0.06308  15.547  < 2e-16 ***
## category_code_LT01_7_count   0.65880    0.15268   4.315 1.93e-05 ***
## category_code_LT01_8_count  -0.12739    0.27953  -0.456    0.649    
## category_code_LT01_12_count  0.14279    0.20956   0.681    0.496    
## category_code_LT01_16_count  0.27519    1.19231   0.231    0.818    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6135, Adjusted R-squared:  0.6087 
## F-statistic: 129.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 0.608894041468702 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0636 -0.7897 -0.0090  0.9202  3.8008 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00018    0.08885 112.548  < 2e-16 ***
## category_code_LT01_2_count   0.89100    0.07030  12.674  < 2e-16 ***
## category_code_LT01_5_count   0.97889    0.06320  15.488  < 2e-16 ***
## category_code_LT01_7_count   0.64046    0.15475   4.139 4.11e-05 ***
## category_code_LT01_8_count  -0.11271    0.27942  -0.403    0.687    
## category_code_LT01_13_count  0.10156    0.24910   0.408    0.684    
## category_code_LT01_14_count  0.24301    0.33169   0.733    0.464    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6136, Adjusted R-squared:  0.6089 
## F-statistic:   130 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 0.608913437621905 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0647 -0.7746 -0.0190  0.9308  3.8033 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99762    0.08878 112.606  < 2e-16 ***
## category_code_LT01_2_count   0.88984    0.07052  12.619  < 2e-16 ***
## category_code_LT01_5_count   0.98414    0.06279  15.675  < 2e-16 ***
## category_code_LT01_7_count   0.65174    0.15404   4.231 2.78e-05 ***
## category_code_LT01_8_count  -0.11204    0.27940  -0.401    0.689    
## category_code_LT01_13_count  0.11135    0.24946   0.446    0.656    
## category_code_LT01_15_count  0.57022    0.76122   0.749    0.454    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6136, Adjusted R-squared:  0.6089 
## F-statistic:   130 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 0.608509262631015 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0649 -0.7754 -0.0184  0.9370  3.8030 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99796    0.08884 112.540  < 2e-16 ***
## category_code_LT01_2_count   0.89699    0.07009  12.798  < 2e-16 ***
## category_code_LT01_5_count   0.98399    0.06282  15.663  < 2e-16 ***
## category_code_LT01_7_count   0.65191    0.15415   4.229  2.8e-05 ***
## category_code_LT01_8_count  -0.11290    0.27986  -0.403    0.687    
## category_code_LT01_13_count  0.10335    0.24939   0.414    0.679    
## category_code_LT01_16_count  0.27637    1.19322   0.232    0.817    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6132, Adjusted R-squared:  0.6085 
## F-statistic: 129.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 0.609163863466448 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0647 -0.7900 -0.0186  0.9242  3.8005 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00044    0.08882 112.594  < 2e-16 ***
## category_code_LT01_2_count   0.88548    0.07091  12.487  < 2e-16 ***
## category_code_LT01_5_count   0.98007    0.06313  15.525  < 2e-16 ***
## category_code_LT01_7_count   0.65061    0.15325   4.245 2.61e-05 ***
## category_code_LT01_8_count  -0.12237    0.27884  -0.439    0.661    
## category_code_LT01_14_count  0.23777    0.33165   0.717    0.474    
## category_code_LT01_15_count  0.54028    0.76003   0.711    0.478    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6139, Adjusted R-squared:  0.6092 
## F-statistic: 130.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 0.608815250266855 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0648 -0.7905 -0.0167  0.9196  3.8001 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00089    0.08887 112.532  < 2e-16 ***
## category_code_LT01_2_count   0.89132    0.07065  12.617  < 2e-16 ***
## category_code_LT01_5_count   0.97961    0.06317  15.508  < 2e-16 ***
## category_code_LT01_7_count   0.64982    0.15333   4.238 2.69e-05 ***
## category_code_LT01_8_count  -0.12336    0.27932  -0.442    0.659    
## category_code_LT01_14_count  0.24775    0.33228   0.746    0.456    
## category_code_LT01_16_count  0.30977    1.19395   0.259    0.795    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6135, Adjusted R-squared:  0.6088 
## F-statistic: 129.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 0.60880258651412 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0660 -0.7754 -0.0308  0.9309  3.8027 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99830    0.08880 112.590  < 2e-16 ***
## category_code_LT01_2_count   0.89092    0.07077  12.589  < 2e-16 ***
## category_code_LT01_5_count   0.98508    0.06275  15.699  < 2e-16 ***
## category_code_LT01_7_count   0.66207    0.15266   4.337 1.75e-05 ***
## category_code_LT01_8_count  -0.12304    0.27932  -0.440    0.660    
## category_code_LT01_15_count  0.55908    0.76079   0.735    0.463    
## category_code_LT01_16_count  0.29232    1.19287   0.245    0.807    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6135, Adjusted R-squared:  0.6088 
## F-statistic: 129.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.619593850452338 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0263 -0.7676  0.0325  0.9184  3.8229 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97806    0.09090 109.771  < 2e-16 ***
## category_code_LT01_2_count   0.69539    0.08753   7.944 1.35e-14 ***
## category_code_LT01_5_count   0.95707    0.06151  15.560  < 2e-16 ***
## category_code_LT01_7_count   0.46994    0.15823   2.970  0.00312 ** 
## category_code_LT01_9_count   0.33745    0.22878   1.475  0.14085    
## category_code_LT01_10_count  0.09253    0.11362   0.814  0.41585    
## category_code_LT01_11_count  0.38546    0.11694   3.296  0.00105 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6242, Adjusted R-squared:  0.6196 
## F-statistic: 135.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 0.611471222866999 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0258 -0.7699  0.0243  0.9548  3.8307 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97021    0.09183 108.570  < 2e-16 ***
## category_code_LT01_2_count   0.85525    0.07355  11.628  < 2e-16 ***
## category_code_LT01_5_count   0.96763    0.06236  15.517  < 2e-16 ***
## category_code_LT01_7_count   0.61624    0.15338   4.018  6.8e-05 ***
## category_code_LT01_9_count   0.37196    0.23096   1.611    0.108    
## category_code_LT01_10_count  0.09906    0.11489   0.862    0.389    
## category_code_LT01_12_count  0.12758    0.20880   0.611    0.541    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6162, Adjusted R-squared:  0.6115 
## F-statistic: 131.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 0.611397959468372 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0278 -0.7937  0.0305  0.9508  3.8308 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97017    0.09184 108.559  < 2e-16 ***
## category_code_LT01_2_count   0.86222    0.07169  12.027  < 2e-16 ***
## category_code_LT01_5_count   0.97052    0.06205  15.642  < 2e-16 ***
## category_code_LT01_7_count   0.60622    0.15489   3.914 0.000104 ***
## category_code_LT01_9_count   0.38169    0.23161   1.648 0.100005    
## category_code_LT01_10_count  0.10005    0.11486   0.871 0.384135    
## category_code_LT01_13_count  0.13171    0.24859   0.530 0.596466    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6161, Adjusted R-squared:  0.6114 
## F-statistic: 131.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 0.611333529927677 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0304 -0.7872  0.0284  0.9378  3.8268 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97414    0.09227 108.097  < 2e-16 ***
## category_code_LT01_2_count   0.86271    0.07174  12.025  < 2e-16 ***
## category_code_LT01_5_count   0.96856    0.06241  15.519  < 2e-16 ***
## category_code_LT01_7_count   0.61255    0.15382   3.982 7.86e-05 ***
## category_code_LT01_9_count   0.36839    0.23119   1.593    0.112    
## category_code_LT01_10_count  0.09112    0.11733   0.777    0.438    
## category_code_LT01_14_count  0.15113    0.33853   0.446    0.655    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.616,  Adjusted R-squared:  0.6113 
## F-statistic: 131.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 0.611536146185434 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0300 -0.7681  0.0043  0.9480  3.8294 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97159    0.09185 108.567  < 2e-16 ***
## category_code_LT01_2_count   0.85867    0.07216  11.900  < 2e-16 ***
## category_code_LT01_5_count   0.97166    0.06199  15.673  < 2e-16 ***
## category_code_LT01_7_count   0.61936    0.15337   4.038 6.25e-05 ***
## category_code_LT01_9_count   0.37658    0.23101   1.630    0.104    
## category_code_LT01_10_count  0.09513    0.11522   0.826    0.409    
## category_code_LT01_15_count  0.51323    0.76045   0.675    0.500    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6162, Adjusted R-squared:  0.6115 
## F-statistic: 131.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 0.611185847896239 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0288 -0.7724  0.0248  0.9467  3.8305 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97044    0.09189 108.504  < 2e-16 ***
## category_code_LT01_2_count   0.86544    0.07177  12.058  < 2e-16 ***
## category_code_LT01_5_count   0.97159    0.06203  15.663  < 2e-16 ***
## category_code_LT01_7_count   0.61816    0.15348   4.028 6.53e-05 ***
## category_code_LT01_9_count   0.37190    0.23112   1.609    0.108    
## category_code_LT01_10_count  0.10145    0.11491   0.883    0.378    
## category_code_LT01_16_count  0.13396    1.18803   0.113    0.910    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6159, Adjusted R-squared:  0.6112 
## F-statistic: 131.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.619112956169219 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0476 -0.7877  0.0103  0.9134  3.8028 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99821    0.08764 114.084  < 2e-16 ***
## category_code_LT01_2_count   0.70368    0.08730   8.061 5.82e-15 ***
## category_code_LT01_5_count   0.95864    0.06181  15.510  < 2e-16 ***
## category_code_LT01_7_count   0.47667    0.15824   3.012  0.00273 ** 
## category_code_LT01_9_count   0.35827    0.22746   1.575  0.11589    
## category_code_LT01_11_count  0.39425    0.12104   3.257  0.00120 ** 
## category_code_LT01_12_count -0.04401    0.21374  -0.206  0.83696    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.61921643337732 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0455 -0.7871  0.0141  0.9109  3.8034 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99754    0.08762 114.102  < 2e-16 ***
## category_code_LT01_2_count   0.70015    0.08732   8.018 7.93e-15 ***
## category_code_LT01_5_count   0.95662    0.06157  15.537  < 2e-16 ***
## category_code_LT01_7_count   0.47023    0.15920   2.954  0.00329 ** 
## category_code_LT01_9_count   0.36545    0.22804   1.603  0.10967    
## category_code_LT01_11_count  0.38572    0.11707   3.295  0.00106 ** 
## category_code_LT01_13_count  0.10323    0.24619   0.419  0.67517    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6238, Adjusted R-squared:  0.6192 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.61930435651925 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0458 -0.7893  0.0230  0.8967  3.8012 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99978    0.08767 114.057  < 2e-16 ***
## category_code_LT01_2_count   0.69792    0.08755   7.972 1.11e-14 ***
## category_code_LT01_5_count   0.95380    0.06191  15.407  < 2e-16 ***
## category_code_LT01_7_count   0.47191    0.15842   2.979  0.00304 ** 
## category_code_LT01_9_count   0.35083    0.22784   1.540  0.12426    
## category_code_LT01_11_count  0.38617    0.11699   3.301  0.00103 ** 
## category_code_LT01_14_count  0.17640    0.32799   0.538  0.59093    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6239, Adjusted R-squared:  0.6193 
## F-statistic: 135.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.619269691949542 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0464 -0.7873 -0.0004  0.9196  3.8032 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99779    0.08761 114.118  < 2e-16 ***
## category_code_LT01_2_count   0.69863    0.08749   7.985    1e-14 ***
## category_code_LT01_5_count   0.95759    0.06153  15.562  < 2e-16 ***
## category_code_LT01_7_count   0.48104    0.15803   3.044  0.00246 ** 
## category_code_LT01_9_count   0.36067    0.22746   1.586  0.11347    
## category_code_LT01_11_count  0.38322    0.11733   3.266  0.00117 ** 
## category_code_LT01_15_count  0.37206    0.75238   0.495  0.62117    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6239, Adjusted R-squared:  0.6193 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.619108478426411 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0466 -0.7877  0.0149  0.9174  3.8028 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99815    0.08764 114.087  < 2e-16 ***
## category_code_LT01_2_count   0.70080    0.08765   7.996  9.3e-15 ***
## category_code_LT01_5_count   0.95727    0.06156  15.551  < 2e-16 ***
## category_code_LT01_7_count   0.47915    0.15801   3.032 0.002555 ** 
## category_code_LT01_9_count   0.35710    0.22757   1.569 0.117249    
## category_code_LT01_11_count  0.38816    0.11699   3.318 0.000974 ***
## category_code_LT01_16_count  0.22490    1.17527   0.191 0.848326    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 0.611111633218032 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0460 -0.7805  0.0109  0.9401  3.8100 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99097    0.08853 112.851  < 2e-16 ***
## category_code_LT01_2_count   0.85936    0.07336  11.714  < 2e-16 ***
## category_code_LT01_5_count   0.96683    0.06242  15.489  < 2e-16 ***
## category_code_LT01_7_count   0.61456    0.15457   3.976 8.06e-05 ***
## category_code_LT01_9_count   0.40345    0.23015   1.753   0.0802 .  
## category_code_LT01_12_count  0.13152    0.20881   0.630   0.5291    
## category_code_LT01_13_count  0.13363    0.24867   0.537   0.5913    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6158, Adjusted R-squared:  0.6111 
## F-statistic: 131.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 0.611140629999185 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0467 -0.7990  0.0179  0.9315  3.8075 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99347    0.08860 112.791  < 2e-16 ***
## category_code_LT01_2_count   0.85846    0.07349  11.682  < 2e-16 ***
## category_code_LT01_5_count   0.96421    0.06272  15.373  < 2e-16 ***
## category_code_LT01_7_count   0.61863    0.15359   4.028 6.52e-05 ***
## category_code_LT01_9_count   0.38634    0.23001   1.680   0.0937 .  
## category_code_LT01_12_count  0.12548    0.20936   0.599   0.5492    
## category_code_LT01_14_count  0.18961    0.33239   0.570   0.5686    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.6158, Adjusted R-squared:  0.6111 
## F-statistic: 131.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 0.611338842024135 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0470 -0.7809 -0.0004  0.9358  3.8097 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99130    0.08850 112.892  < 2e-16 ***
## category_code_LT01_2_count   0.85392    0.07402  11.537  < 2e-16 ***
## category_code_LT01_5_count   0.96776    0.06237  15.517  < 2e-16 ***
## category_code_LT01_7_count   0.62741    0.15297   4.102  4.8e-05 ***
## category_code_LT01_9_count   0.39733    0.22952   1.731   0.0841 .  
## category_code_LT01_12_count  0.13717    0.20868   0.657   0.5113    
## category_code_LT01_15_count  0.57514    0.75784   0.759   0.4483    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.616,  Adjusted R-squared:  0.6113 
## F-statistic: 131.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 0.610902172455882 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0473 -0.7811  0.0060  0.9311  3.8094 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99158    0.08856 112.820  < 2e-16 ***
## category_code_LT01_2_count   0.86203    0.07355  11.720  < 2e-16 ***
## category_code_LT01_5_count   0.96775    0.06241  15.506  < 2e-16 ***
## category_code_LT01_7_count   0.62692    0.15309   4.095 4.94e-05 ***
## category_code_LT01_9_count   0.39353    0.22973   1.713   0.0873 .  
## category_code_LT01_12_count  0.13548    0.20882   0.649   0.5168    
## category_code_LT01_16_count  0.18513    1.18797   0.156   0.8762    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6156, Adjusted R-squared:  0.6109 
## F-statistic: 131.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 0.611100286353172 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0487 -0.8216  0.0158  0.9308  3.8072 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99377    0.08860 112.795  < 2e-16 ***
## category_code_LT01_2_count   0.86466    0.07174  12.052  < 2e-16 ***
## category_code_LT01_5_count   0.96666    0.06246  15.476  < 2e-16 ***
## category_code_LT01_7_count   0.60750    0.15515   3.916 0.000103 ***
## category_code_LT01_9_count   0.39602    0.23061   1.717 0.086557 .  
## category_code_LT01_13_count  0.13801    0.24857   0.555 0.579002    
## category_code_LT01_14_count  0.20492    0.33139   0.618 0.536619    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6158, Adjusted R-squared:  0.6111 
## F-statistic: 131.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 0.611281389985823 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0492 -0.7810  0.0038  0.9300  3.8095 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99146    0.08851 112.887  < 2e-16 ***
## category_code_LT01_2_count   0.86097    0.07214  11.935  < 2e-16 ***
## category_code_LT01_5_count   0.97081    0.06205  15.645  < 2e-16 ***
## category_code_LT01_7_count   0.61611    0.15452   3.987  7.7e-05 ***
## category_code_LT01_9_count   0.40862    0.23013   1.776   0.0764 .  
## category_code_LT01_13_count  0.14922    0.24890   0.600   0.5491    
## category_code_LT01_15_count  0.59345    0.75902   0.782   0.4347    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.616,  Adjusted R-squared:  0.6113 
## F-statistic: 131.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 0.610818876688156 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0496 -0.7813  0.0101  0.9542  3.8092 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99177    0.08857 112.813  < 2e-16 ***
## category_code_LT01_2_count   0.86946    0.07162  12.140  < 2e-16 ***
## category_code_LT01_5_count   0.97082    0.06210  15.633  < 2e-16 ***
## category_code_LT01_7_count   0.61643    0.15464   3.986 7.73e-05 ***
## category_code_LT01_9_count   0.40403    0.23031   1.754    0.080 .  
## category_code_LT01_13_count  0.13983    0.24884   0.562    0.574    
## category_code_LT01_16_count  0.19558    1.18873   0.165    0.869    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6155, Adjusted R-squared:  0.6108 
## F-statistic:   131 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 0.611284558405472 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0499 -0.7837  0.0097  0.9261  3.8069 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99410    0.08858 112.830  < 2e-16 ***
## category_code_LT01_2_count   0.86031    0.07227  11.904  < 2e-16 ***
## category_code_LT01_5_count   0.96793    0.06241  15.510  < 2e-16 ***
## category_code_LT01_7_count   0.62099    0.15357   4.044 6.11e-05 ***
## category_code_LT01_9_count   0.38981    0.23000   1.695   0.0907 .  
## category_code_LT01_14_count  0.19978    0.33139   0.603   0.5469    
## category_code_LT01_15_count  0.55762    0.75800   0.736   0.4623    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.404 on 491 degrees of freedom
## Multiple R-squared:  0.616,  Adjusted R-squared:  0.6113 
## F-statistic: 131.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 0.610881911753246 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0501 -0.7840  0.0152  0.9271  3.8065 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99449    0.08863 112.761  < 2e-16 ***
## category_code_LT01_2_count   0.86750    0.07191  12.063  < 2e-16 ***
## category_code_LT01_5_count   0.96764    0.06246  15.493  < 2e-16 ***
## category_code_LT01_7_count   0.62024    0.15367   4.036  6.3e-05 ***
## category_code_LT01_9_count   0.38550    0.23022   1.674   0.0947 .  
## category_code_LT01_14_count  0.20879    0.33206   0.629   0.5298    
## category_code_LT01_16_count  0.21463    1.18987   0.180   0.8569    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6156, Adjusted R-squared:  0.6109 
## F-statistic:   131 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 0.611020223158757 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0508 -0.7817  0.0021  0.9276  3.8088 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99216    0.08854 112.850  < 2e-16 ***
## category_code_LT01_2_count   0.86471    0.07221  11.975  < 2e-16 ***
## category_code_LT01_5_count   0.97198    0.06204  15.667  < 2e-16 ***
## category_code_LT01_7_count   0.62993    0.15306   4.116 4.53e-05 ***
## category_code_LT01_9_count   0.39750    0.22971   1.730   0.0842 .  
## category_code_LT01_15_count  0.57278    0.75861   0.755   0.4506    
## category_code_LT01_16_count  0.20420    1.18842   0.172   0.8636    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6157, Adjusted R-squared:  0.611 
## F-statistic: 131.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.617955231028749 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0324 -0.7678  0.0140  0.9282  3.8227 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97826    0.09110 109.535  < 2e-16 ***
## category_code_LT01_2_count   0.71358    0.08709   8.193 2.22e-15 ***
## category_code_LT01_5_count   0.96549    0.06171  15.645  < 2e-16 ***
## category_code_LT01_7_count   0.48708    0.15831   3.077 0.002209 ** 
## category_code_LT01_10_count  0.11238    0.11321   0.993 0.321362    
## category_code_LT01_11_count  0.40112    0.12110   3.312 0.000994 ***
## category_code_LT01_12_count -0.05263    0.21419  -0.246 0.805998    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.617970038944357 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0309 -0.7676  0.0299  0.9331  3.8229 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97806    0.09109 109.538  < 2e-16 ***
## category_code_LT01_2_count   0.71107    0.08708   8.165 2.72e-15 ***
## category_code_LT01_5_count   0.96365    0.06148  15.675  < 2e-16 ***
## category_code_LT01_7_count   0.48423    0.15909   3.044 0.002462 ** 
## category_code_LT01_10_count  0.11076    0.11316   0.979 0.328193    
## category_code_LT01_11_count  0.39222    0.11715   3.348 0.000876 ***
## category_code_LT01_13_count  0.06932    0.24598   0.282 0.778211    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.618056215192389 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0329 -0.7715  0.0292  0.9087  3.8191 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98189    0.09149 109.098  < 2e-16 ***
## category_code_LT01_2_count   0.70913    0.08727   8.126 3.64e-15 ***
## category_code_LT01_5_count   0.96103    0.06185  15.537  < 2e-16 ***
## category_code_LT01_7_count   0.48468    0.15837   3.060 0.002332 ** 
## category_code_LT01_10_count  0.10079    0.11572   0.871 0.384199    
## category_code_LT01_11_count  0.39228    0.11708   3.351 0.000869 ***
## category_code_LT01_14_count  0.14629    0.33541   0.436 0.662930    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6227, Adjusted R-squared:  0.6181 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.618022113663905 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0321 -0.7684  0.0163  0.9364  3.8221 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97882    0.09111 109.531  < 2e-16 ***
## category_code_LT01_2_count   0.70973    0.08723   8.136 3.37e-15 ***
## category_code_LT01_5_count   0.96427    0.06145  15.692  < 2e-16 ***
## category_code_LT01_7_count   0.49188    0.15813   3.111 0.001976 ** 
## category_code_LT01_10_count  0.10784    0.11352   0.950 0.342614    
## category_code_LT01_11_count  0.39006    0.11740   3.323 0.000958 ***
## category_code_LT01_15_count  0.28924    0.75604   0.383 0.702201    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.61794002856198 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0315 -0.7681  0.0253  0.9323  3.8224 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97854    0.09112 109.509  < 2e-16 ***
## category_code_LT01_2_count   0.71049    0.08747   8.123 3.72e-15 ***
## category_code_LT01_5_count   0.96387    0.06147  15.681  < 2e-16 ***
## category_code_LT01_7_count   0.49009    0.15805   3.101 0.002041 ** 
## category_code_LT01_10_count  0.11054    0.11323   0.976 0.329391    
## category_code_LT01_11_count  0.39382    0.11708   3.364 0.000829 ***
## category_code_LT01_16_count  0.23794    1.17737   0.202 0.839929    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.6179 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 0.609540095520371 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0308 -0.7741  0.0124  0.9280  3.8309 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97006    0.09206 108.299  < 2e-16 ***
## category_code_LT01_2_count   0.87538    0.07265  12.049  < 2e-16 ***
## category_code_LT01_5_count   0.97505    0.06233  15.643  < 2e-16 ***
## category_code_LT01_7_count   0.63320    0.15433   4.103 4.78e-05 ***
## category_code_LT01_10_count  0.11918    0.11445   1.041    0.298    
## category_code_LT01_12_count  0.12677    0.20940   0.605    0.545    
## category_code_LT01_13_count  0.09709    0.24859   0.391    0.696    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6095 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 0.609592444561158 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0332 -0.7905  0.0133  0.9137  3.8267 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97422    0.09248 107.854  < 2e-16 ***
## category_code_LT01_2_count   0.87432    0.07277  12.016  < 2e-16 ***
## category_code_LT01_5_count   0.97252    0.06268  15.517  < 2e-16 ***
## category_code_LT01_7_count   0.63556    0.15344   4.142 4.05e-05 ***
## category_code_LT01_10_count  0.10869    0.11700   0.929    0.353    
## category_code_LT01_12_count  0.12202    0.20984   0.581    0.561    
## category_code_LT01_14_count  0.15884    0.33989   0.467    0.640    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6096 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 0.609747673764904 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0326 -0.7610  0.0034  0.9263  3.8295 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97141    0.09206 108.316  < 2e-16 ***
## category_code_LT01_2_count   0.87049    0.07326  11.883  < 2e-16 ***
## category_code_LT01_5_count   0.97566    0.06229  15.662  < 2e-16 ***
## category_code_LT01_7_count   0.64300    0.15296   4.204 3.12e-05 ***
## category_code_LT01_10_count  0.11381    0.11481   0.991    0.322    
## category_code_LT01_12_count  0.13154    0.20929   0.628    0.530    
## category_code_LT01_15_count  0.49022    0.76208   0.643    0.520    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6097 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 0.609441023416308 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0315 -0.7753  0.0047  0.9273  3.8305 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97044    0.09210 108.261  < 2e-16 ***
## category_code_LT01_2_count   0.87631    0.07297  12.009  < 2e-16 ***
## category_code_LT01_5_count   0.97549    0.06233  15.650  < 2e-16 ***
## category_code_LT01_7_count   0.64180    0.15305   4.194 3.26e-05 ***
## category_code_LT01_10_count  0.11937    0.11453   1.042    0.298    
## category_code_LT01_12_count  0.12979    0.20938   0.620    0.536    
## category_code_LT01_16_count  0.19907    1.19054   0.167    0.867    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6094 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 0.609458322807038 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0355 -0.7881  0.0237  0.9233  3.8264 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97458    0.09249 107.842  < 2e-16 ***
## category_code_LT01_2_count   0.88181    0.07091  12.435  < 2e-16 ***
## category_code_LT01_5_count   0.97534    0.06241  15.628  < 2e-16 ***
## category_code_LT01_7_count   0.62801    0.15483   4.056  5.8e-05 ***
## category_code_LT01_10_count  0.10929    0.11701   0.934    0.351    
## category_code_LT01_13_count  0.10229    0.24853   0.412    0.681    
## category_code_LT01_14_count  0.17411    0.33908   0.513    0.608    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6095 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 0.609590846435743 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0349 -0.7693  0.0133  0.9315  3.8296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97139    0.09208 108.294  < 2e-16 ***
## category_code_LT01_2_count   0.87883    0.07128  12.330  < 2e-16 ***
## category_code_LT01_5_count   0.97905    0.06197  15.798  < 2e-16 ***
## category_code_LT01_7_count   0.63546    0.15432   4.118 4.49e-05 ***
## category_code_LT01_10_count  0.11552    0.11477   1.006    0.315    
## category_code_LT01_13_count  0.11064    0.24888   0.445    0.657    
## category_code_LT01_15_count  0.50080    0.76334   0.656    0.512    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6096 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 0.609271942531751 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0338 -0.7894  0.0089  0.9297  3.8305 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97041    0.09212 108.237  < 2e-16 ***
## category_code_LT01_2_count   0.88482    0.07095  12.470  < 2e-16 ***
## category_code_LT01_5_count   0.97887    0.06201  15.786  < 2e-16 ***
## category_code_LT01_7_count   0.63484    0.15440   4.112 4.61e-05 ***
## category_code_LT01_10_count  0.12123    0.11448   1.059    0.290    
## category_code_LT01_13_count  0.10306    0.24879   0.414    0.679    
## category_code_LT01_16_count  0.20401    1.19153   0.171    0.864    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.614,  Adjusted R-squared:  0.6093 
## F-statistic: 130.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 0.609639080289839 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0374 -0.7654  0.0119  0.9215  3.8251 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97586    0.09249 107.855  < 2e-16 ***
## category_code_LT01_2_count   0.87767    0.07142  12.288  < 2e-16 ***
## category_code_LT01_5_count   0.97618    0.06236  15.653  < 2e-16 ***
## category_code_LT01_7_count   0.63832    0.15345   4.160 3.76e-05 ***
## category_code_LT01_10_count  0.10434    0.11735   0.889    0.374    
## category_code_LT01_14_count  0.17229    0.33899   0.508    0.612    
## category_code_LT01_15_count  0.48006    0.76206   0.630    0.529    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6096 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 0.609351989295572 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0364 -0.7750  0.0100  0.9225  3.8259 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97509    0.09254 107.787  < 2e-16 ***
## category_code_LT01_2_count   0.88286    0.07121  12.398  < 2e-16 ***
## category_code_LT01_5_count   0.97582    0.06241  15.636  < 2e-16 ***
## category_code_LT01_7_count   0.63705    0.15351   4.150 3.92e-05 ***
## category_code_LT01_10_count  0.10927    0.11715   0.933    0.351    
## category_code_LT01_14_count  0.17734    0.33988   0.522    0.602    
## category_code_LT01_16_count  0.22544    1.19308   0.189    0.850    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6141, Adjusted R-squared:  0.6094 
## F-statistic: 130.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609459763151016 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0357 -0.7673 -0.0034  0.9296  3.8292 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97177    0.09212 108.249  < 2e-16 ***
## category_code_LT01_2_count   0.88047    0.07150  12.314  < 2e-16 ***
## category_code_LT01_5_count   0.97966    0.06197  15.810  < 2e-16 ***
## category_code_LT01_7_count   0.64522    0.15305   4.216 2.97e-05 ***
## category_code_LT01_10_count  0.11603    0.11485   1.010    0.313    
## category_code_LT01_15_count  0.48718    0.76289   0.639    0.523    
## category_code_LT01_16_count  0.21556    1.19129   0.181    0.856    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6095 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.617261533518011 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0568 -0.7634  0.0164  0.9134  3.7985 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00243    0.08781 113.911  < 2e-16 ***
## category_code_LT01_2_count   0.72211    0.08672   8.327 8.32e-16 ***
## category_code_LT01_5_count   0.96586    0.06178  15.633  < 2e-16 ***
## category_code_LT01_7_count   0.49367    0.15909   3.103 0.002025 ** 
## category_code_LT01_11_count  0.40237    0.12125   3.318 0.000973 ***
## category_code_LT01_12_count -0.04657    0.21430  -0.217 0.828036    
## category_code_LT01_13_count  0.07536    0.24620   0.306 0.759678    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.617518339838599 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0565 -0.7839  0.0096  0.9101  3.7961 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00485    0.08784 113.893  < 2e-16 ***
## category_code_LT01_2_count   0.71764    0.08704   8.245 1.52e-15 ***
## category_code_LT01_5_count   0.96196    0.06211  15.488  < 2e-16 ***
## category_code_LT01_7_count   0.49039    0.15852   3.093  0.00209 ** 
## category_code_LT01_11_count  0.40283    0.12115   3.325  0.00095 ***
## category_code_LT01_12_count -0.05560    0.21477  -0.259  0.79582    
## category_code_LT01_14_count  0.21409    0.32902   0.651  0.51554    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6175 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.617349669523134 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0573 -0.7539 -0.0046  0.9199  3.7984 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00252    0.08780 113.928  < 2e-16 ***
## category_code_LT01_2_count   0.71995    0.08695   8.280 1.17e-15 ***
## category_code_LT01_5_count   0.96640    0.06176  15.649  < 2e-16 ***
## category_code_LT01_7_count   0.50205    0.15805   3.177  0.00158 ** 
## category_code_LT01_11_count  0.39887    0.12162   3.280  0.00111 ** 
## category_code_LT01_12_count -0.04175    0.21437  -0.195  0.84565    
## category_code_LT01_15_count  0.34316    0.75463   0.455  0.64949    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.61723190360036 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0574 -0.7592  0.0158  0.9199  3.7981 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00290    0.08782 113.905  < 2e-16 ***
## category_code_LT01_2_count   0.72125    0.08715   8.276 1.22e-15 ***
## category_code_LT01_5_count   0.96603    0.06178  15.637  < 2e-16 ***
## category_code_LT01_7_count   0.50015    0.15799   3.166 0.001644 ** 
## category_code_LT01_11_count  0.40383    0.12120   3.332 0.000927 ***
## category_code_LT01_12_count -0.04447    0.21429  -0.208 0.835686    
## category_code_LT01_16_count  0.27788    1.17776   0.236 0.813581    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6172 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.617538361124319 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0546 -0.7938  0.0186  0.9097  3.7967 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00421    0.08783 113.907  < 2e-16 ***
## category_code_LT01_2_count   0.71497    0.08706   8.212 1.93e-15 ***
## category_code_LT01_5_count   0.96010    0.06192  15.506  < 2e-16 ***
## category_code_LT01_7_count   0.48730    0.15930   3.059 0.002343 ** 
## category_code_LT01_11_count  0.39340    0.11722   3.356 0.000852 ***
## category_code_LT01_13_count  0.07493    0.24607   0.305 0.760855    
## category_code_LT01_14_count  0.20821    0.32811   0.635 0.526015    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6175 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.617404692425833 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0556 -0.7751 -0.0001  0.9167  3.7989 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00201    0.08778 113.943  < 2e-16 ***
## category_code_LT01_2_count   0.71711    0.08693   8.249 1.48e-15 ***
## category_code_LT01_5_count   0.96475    0.06151  15.683  < 2e-16 ***
## category_code_LT01_7_count   0.49780    0.15883   3.134 0.001827 ** 
## category_code_LT01_11_count  0.39103    0.11757   3.326 0.000947 ***
## category_code_LT01_13_count  0.08123    0.24653   0.329 0.741938    
## category_code_LT01_15_count  0.36302    0.75536   0.481 0.631016    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.61727401339032 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0557 -0.7822  0.0175  0.9175  3.7986 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00241    0.08780 113.918  < 2e-16 ***
## category_code_LT01_2_count   0.71848    0.08715   8.245 1.53e-15 ***
## category_code_LT01_5_count   0.96431    0.06154  15.670  < 2e-16 ***
## category_code_LT01_7_count   0.49625    0.15881   3.125 0.001885 ** 
## category_code_LT01_11_count  0.39594    0.11721   3.378 0.000788 ***
## category_code_LT01_13_count  0.07676    0.24635   0.312 0.755477    
## category_code_LT01_16_count  0.29637    1.17845   0.251 0.801540    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.617624037850081 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0552 -0.7644  0.0070  0.9133  3.7967 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00430    0.08782 113.924  < 2e-16 ***
## category_code_LT01_2_count   0.71304    0.08724   8.173 2.58e-15 ***
## category_code_LT01_5_count   0.96083    0.06189  15.525  < 2e-16 ***
## category_code_LT01_7_count   0.49555    0.15827   3.131 0.001846 ** 
## category_code_LT01_11_count  0.39067    0.11747   3.326 0.000948 ***
## category_code_LT01_14_count  0.20499    0.32813   0.625 0.532447    
## category_code_LT01_15_count  0.33953    0.75399   0.450 0.652691    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6176 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617525433968892 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0552 -0.7665  0.0142  0.9144  3.7962 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00479    0.08784 113.901  < 2e-16 ***
## category_code_LT01_2_count   0.71361    0.08754   8.152    3e-15 ***
## category_code_LT01_5_count   0.96017    0.06192  15.507  < 2e-16 ***
## category_code_LT01_7_count   0.49357    0.15821   3.120 0.001916 ** 
## category_code_LT01_11_count  0.39516    0.11713   3.374 0.000801 ***
## category_code_LT01_14_count  0.21297    0.32865   0.648 0.517281    
## category_code_LT01_16_count  0.32534    1.17906   0.276 0.782717    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6175 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617371525796659 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0563 -0.7629 -0.0004  0.9215  3.7984 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00254    0.08779 113.937  < 2e-16 ***
## category_code_LT01_2_count   0.71628    0.08736   8.199 2.12e-15 ***
## category_code_LT01_5_count   0.96498    0.06151  15.689  < 2e-16 ***
## category_code_LT01_7_count   0.50464    0.15779   3.198 0.001472 ** 
## category_code_LT01_11_count  0.39303    0.11747   3.346 0.000883 ***
## category_code_LT01_15_count  0.35576    0.75463   0.471 0.637540    
## category_code_LT01_16_count  0.30265    1.17821   0.257 0.797385    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.609043686443509 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0564 -0.8074 -0.0036  0.9094  3.8027 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99821    0.08879 112.602  < 2e-16 ***
## category_code_LT01_2_count   0.88031    0.07251  12.141  < 2e-16 ***
## category_code_LT01_5_count   0.97133    0.06274  15.482  < 2e-16 ***
## category_code_LT01_7_count   0.63695    0.15457   4.121 4.43e-05 ***
## category_code_LT01_12_count  0.12437    0.21001   0.592    0.554    
## category_code_LT01_13_count  0.10333    0.24870   0.415    0.678    
## category_code_LT01_14_count  0.22551    0.33263   0.678    0.498    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6138, Adjusted R-squared:  0.609 
## F-statistic:   130 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.609129746595399 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0570 -0.7853 -0.0147  0.9167  3.8052 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99577    0.08871 112.674  < 2e-16 ***
## category_code_LT01_2_count   0.87733    0.07296  12.025  < 2e-16 ***
## category_code_LT01_5_count   0.97580    0.06236  15.648  < 2e-16 ***
## category_code_LT01_7_count   0.64732    0.15385   4.207 3.07e-05 ***
## category_code_LT01_12_count  0.13770    0.20935   0.658    0.511    
## category_code_LT01_13_count  0.11271    0.24904   0.453    0.651    
## category_code_LT01_15_count  0.57347    0.76103   0.754    0.451    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6138, Adjusted R-squared:  0.6091 
## F-statistic: 130.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.608717646027678 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0573 -0.7857 -0.0129  0.9191  3.8049 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99610    0.08877 112.609  < 2e-16 ***
## category_code_LT01_2_count   0.88472    0.07255  12.194  < 2e-16 ***
## category_code_LT01_5_count   0.97567    0.06241  15.634  < 2e-16 ***
## category_code_LT01_7_count   0.64745    0.15395   4.206  3.1e-05 ***
## category_code_LT01_12_count  0.13645    0.20948   0.651    0.515    
## category_code_LT01_13_count  0.10467    0.24899   0.420    0.674    
## category_code_LT01_16_count  0.26676    1.19167   0.224    0.823    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6134, Adjusted R-squared:  0.6087 
## F-statistic: 129.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.60931303913143 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0570 -0.7879 -0.0053  0.9042  3.8026 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99834    0.08876 112.645  < 2e-16 ***
## category_code_LT01_2_count   0.87437    0.07320  11.946  < 2e-16 ***
## category_code_LT01_5_count   0.97205    0.06270  15.504  < 2e-16 ***
## category_code_LT01_7_count   0.64702    0.15313   4.225 2.84e-05 ***
## category_code_LT01_12_count  0.12940    0.20988   0.617    0.538    
## category_code_LT01_14_count  0.21943    0.33260   0.660    0.510    
## category_code_LT01_15_count  0.54335    0.75991   0.715    0.475    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.614,  Adjusted R-squared:  0.6093 
## F-statistic: 130.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.608954314271746 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0571 -0.7883 -0.0086  0.9085  3.8022 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99877    0.08881 112.585  < 2e-16 ***
## category_code_LT01_2_count   0.88055    0.07293  12.074  < 2e-16 ***
## category_code_LT01_5_count   0.97163    0.06275  15.485  < 2e-16 ***
## category_code_LT01_7_count   0.64618    0.15320   4.218 2.94e-05 ***
## category_code_LT01_12_count  0.12767    0.20997   0.608    0.543    
## category_code_LT01_14_count  0.22938    0.33318   0.688    0.491    
## category_code_LT01_16_count  0.29292    1.19225   0.246    0.806    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6137, Adjusted R-squared:  0.609 
## F-statistic:   130 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609010975551222 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0579 -0.7823 -0.0189  0.9127  3.8046 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99631    0.08873 112.656  < 2e-16 ***
## category_code_LT01_2_count   0.87822    0.07331  11.979  < 2e-16 ***
## category_code_LT01_5_count   0.97625    0.06236  15.655  < 2e-16 ***
## category_code_LT01_7_count   0.65745    0.15252   4.310 1.97e-05 ***
## category_code_LT01_12_count  0.14134    0.20934   0.675    0.500    
## category_code_LT01_15_count  0.56159    0.76058   0.738    0.461    
## category_code_LT01_16_count  0.28094    1.19119   0.236    0.814    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6137, Adjusted R-squared:  0.609 
## F-statistic:   130 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.609188274821804 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0595 -0.7884 -0.0082  0.9171  3.8021 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99884    0.08877 112.641  < 2e-16 ***
## category_code_LT01_2_count   0.88192    0.07133  12.363  < 2e-16 ***
## category_code_LT01_5_count   0.97498    0.06243  15.617  < 2e-16 ***
## category_code_LT01_7_count   0.63834    0.15454   4.131 4.25e-05 ***
## category_code_LT01_13_count  0.11762    0.24892   0.473    0.637    
## category_code_LT01_14_count  0.23593    0.33160   0.711    0.477    
## category_code_LT01_15_count  0.55537    0.76108   0.730    0.466    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6139, Adjusted R-squared:  0.6092 
## F-statistic: 130.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.608816014065912 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0597 -0.7889 -0.0037  0.9188  3.8017 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99929    0.08882 112.580  < 2e-16 ***
## category_code_LT01_2_count   0.88826    0.07104  12.503  < 2e-16 ***
## category_code_LT01_5_count   0.97454    0.06248  15.597  < 2e-16 ***
## category_code_LT01_7_count   0.63810    0.15462   4.127 4.32e-05 ***
## category_code_LT01_13_count  0.11018    0.24887   0.443    0.658    
## category_code_LT01_14_count  0.24592    0.33223   0.740    0.460    
## category_code_LT01_16_count  0.30359    1.19330   0.254    0.799    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6135, Adjusted R-squared:  0.6088 
## F-statistic: 129.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.608832269817539 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0608 -0.7694 -0.0230  0.9294  3.8043 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99670    0.08875 112.639  < 2e-16 ***
## category_code_LT01_2_count   0.88726    0.07124  12.455  < 2e-16 ***
## category_code_LT01_5_count   0.97990    0.06203  15.796  < 2e-16 ***
## category_code_LT01_7_count   0.64951    0.15391   4.220 2.91e-05 ***
## category_code_LT01_13_count  0.11988    0.24926   0.481    0.631    
## category_code_LT01_15_count  0.57436    0.76188   0.754    0.451    
## category_code_LT01_16_count  0.28935    1.19229   0.243    0.808    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6136, Adjusted R-squared:  0.6088 
## F-statistic: 129.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609065740190534 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0605 -0.7890 -0.0155  0.9160  3.8015 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99948    0.08879 112.620  < 2e-16 ***
## category_code_LT01_2_count   0.88286    0.07167  12.318  < 2e-16 ***
## category_code_LT01_5_count   0.97545    0.06243  15.625  < 2e-16 ***
## category_code_LT01_7_count   0.64881    0.15319   4.235 2.72e-05 ***
## category_code_LT01_14_count  0.24062    0.33219   0.724    0.469    
## category_code_LT01_15_count  0.54304    0.76057   0.714    0.476    
## category_code_LT01_16_count  0.31398    1.19278   0.263    0.792    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6138, Adjusted R-squared:  0.6091 
## F-statistic: 130.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.612832734480904 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0351 -0.7713  0.0313  0.9179  4.3761 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97650    0.09173 108.761  < 2e-16 ***
## category_code_LT01_2_count   0.72656    0.08769   8.286 1.13e-15 ***
## category_code_LT01_5_count   0.97194    0.06268  15.507  < 2e-16 ***
## category_code_LT01_8_count  -0.08426    0.27755  -0.304   0.7616    
## category_code_LT01_9_count   0.39665    0.23013   1.724   0.0854 .  
## category_code_LT01_10_count  0.11580    0.11440   1.012   0.3119    
## category_code_LT01_11_count  0.48337    0.11315   4.272 2.33e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6175, Adjusted R-squared:  0.6128 
## F-statistic: 132.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.612129585261763 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0621 -0.7914  0.0173  0.8967  4.3271 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00181    0.08848 113.044  < 2e-16 ***
## category_code_LT01_2_count   0.73798    0.08736   8.448 3.39e-16 ***
## category_code_LT01_5_count   0.97435    0.06293  15.482  < 2e-16 ***
## category_code_LT01_8_count  -0.07366    0.27800  -0.265   0.7911    
## category_code_LT01_9_count   0.42326    0.22874   1.850   0.0649 .  
## category_code_LT01_11_count  0.49940    0.11691   4.272 2.33e-05 ***
## category_code_LT01_12_count -0.07849    0.21554  -0.364   0.7159    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6168, Adjusted R-squared:  0.6121 
## F-statistic: 131.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.612495916370184 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0578 -0.7900  0.0309  0.9099  4.3436 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00046    0.08843 113.085  < 2e-16 ***
## category_code_LT01_2_count   0.73067    0.08750   8.350 7.00e-16 ***
## category_code_LT01_5_count   0.97015    0.06278  15.454  < 2e-16 ***
## category_code_LT01_8_count  -0.06698    0.27798  -0.241   0.8097    
## category_code_LT01_9_count   0.43473    0.22903   1.898   0.0583 .  
## category_code_LT01_11_count  0.48156    0.11345   4.245 2.62e-05 ***
## category_code_LT01_13_count  0.19064    0.24676   0.773   0.4401    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6172, Adjusted R-squared:  0.6125 
## F-statistic: 131.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.612492611915638 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0592 -0.7936  0.0226  0.8991  4.3437 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00402    0.08849 113.047  < 2e-16 ***
## category_code_LT01_2_count   0.72892    0.08772   8.309 9.47e-16 ***
## category_code_LT01_5_count   0.96710    0.06310  15.327  < 2e-16 ***
## category_code_LT01_8_count  -0.08161    0.27764  -0.294   0.7689    
## category_code_LT01_9_count   0.41203    0.22916   1.798   0.0728 .  
## category_code_LT01_11_count  0.48421    0.11323   4.276 2.28e-05 ***
## category_code_LT01_14_count  0.25402    0.32995   0.770   0.4417    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6172, Adjusted R-squared:  0.6125 
## F-statistic: 131.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.612149960244381 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0604 -0.7908  0.0095  0.8982  4.3375 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00127    0.08847 113.053  < 2e-16 ***
## category_code_LT01_2_count   0.73323    0.08758   8.372 5.94e-16 ***
## category_code_LT01_5_count   0.97272    0.06273  15.506  < 2e-16 ***
## category_code_LT01_8_count  -0.07985    0.27776  -0.287    0.774    
## category_code_LT01_9_count   0.42629    0.22879   1.863    0.063 .  
## category_code_LT01_11_count  0.48533    0.11344   4.278 2.27e-05 ***
## category_code_LT01_15_count  0.30211    0.75908   0.398    0.691    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6168, Adjusted R-squared:  0.6121 
## F-statistic: 131.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.612041002757731 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0605 -0.7911  0.0246  0.9003  4.3335 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00154    0.08849 113.025  < 2e-16 ***
## category_code_LT01_2_count   0.73499    0.08773   8.378 5.72e-16 ***
## category_code_LT01_5_count   0.97244    0.06274  15.499  < 2e-16 ***
## category_code_LT01_8_count  -0.08009    0.27810  -0.288    0.773    
## category_code_LT01_9_count   0.42327    0.22884   1.850    0.065 .  
## category_code_LT01_11_count  0.48899    0.11317   4.321 1.88e-05 ***
## category_code_LT01_16_count  0.16983    1.18731   0.143    0.886    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6167, Adjusted R-squared:  0.612 
## F-statistic: 131.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.610629353619806 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0423 -0.7582  0.0135  0.8989  4.3276 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97655    0.09199 108.452  < 2e-16 ***
## category_code_LT01_2_count   0.74985    0.08714   8.605  < 2e-16 ***
## category_code_LT01_5_count   0.98235    0.06287  15.626  < 2e-16 ***
## category_code_LT01_8_count  -0.06252    0.27842  -0.225    0.822    
## category_code_LT01_10_count  0.14046    0.11397   1.232    0.218    
## category_code_LT01_11_count  0.51005    0.11689   4.364 1.56e-05 ***
## category_code_LT01_12_count -0.09046    0.21604  -0.419    0.676    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6106 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.61079629799995 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0394 -0.7639  0.0248  0.9097  4.3395 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97619    0.09197 108.473  < 2e-16 ***
## category_code_LT01_2_count   0.74431    0.08724   8.532  < 2e-16 ***
## category_code_LT01_5_count   0.97857    0.06271  15.604  < 2e-16 ***
## category_code_LT01_8_count  -0.05803    0.27853  -0.208    0.835    
## category_code_LT01_10_count  0.13689    0.11395   1.201    0.230    
## category_code_LT01_11_count  0.49253    0.11346   4.341 1.72e-05 ***
## category_code_LT01_13_count  0.15345    0.24697   0.621    0.535    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6155, Adjusted R-squared:  0.6108 
## F-statistic:   131 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.610820971445927 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0431 -0.7673  0.0252  0.9108  4.3369 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98201    0.09239 108.043  < 2e-16 ***
## category_code_LT01_2_count   0.74275    0.08742   8.497 2.35e-16 ***
## category_code_LT01_5_count   0.97555    0.06308  15.466  < 2e-16 ***
## category_code_LT01_8_count  -0.06997    0.27812  -0.252    0.801    
## category_code_LT01_10_count  0.12287    0.11663   1.053    0.293    
## category_code_LT01_11_count  0.49445    0.11325   4.366 1.55e-05 ***
## category_code_LT01_14_count  0.21818    0.33780   0.646    0.519    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6155, Adjusted R-squared:  0.6108 
## F-statistic:   131 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.610543072058846 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0413 -0.7664  0.0112  0.9047  4.3345 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97679    0.09202 108.422  < 2e-16 ***
## category_code_LT01_2_count   0.74643    0.08730   8.551  < 2e-16 ***
## category_code_LT01_5_count   0.98045    0.06268  15.642  < 2e-16 ***
## category_code_LT01_8_count  -0.06845    0.27822  -0.246    0.806    
## category_code_LT01_10_count  0.13675    0.11429   1.196    0.232    
## category_code_LT01_11_count  0.49581    0.11344   4.371 1.51e-05 ***
## category_code_LT01_15_count  0.19676    0.76285   0.258    0.797    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6152, Adjusted R-squared:  0.6105 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.610508157219036 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0409 -0.7639  0.0119  0.9051  4.3340 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97665    0.09203 108.406  < 2e-16 ***
## category_code_LT01_2_count   0.74674    0.08754   8.530  < 2e-16 ***
## category_code_LT01_5_count   0.98017    0.06268  15.637  < 2e-16 ***
## category_code_LT01_8_count  -0.06960    0.27854  -0.250    0.803    
## category_code_LT01_10_count  0.13848    0.11401   1.215    0.225    
## category_code_LT01_11_count  0.49813    0.11320   4.400 1.33e-05 ***
## category_code_LT01_16_count  0.17851    1.18996   0.150    0.881    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6152, Adjusted R-squared:  0.6105 
## F-statistic: 130.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.609775139679812 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0718 -0.7729  0.0073  0.8944  4.2782 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00640    0.08871 112.805  < 2e-16 ***
## category_code_LT01_2_count   0.75926    0.08676   8.751  < 2e-16 ***
## category_code_LT01_5_count   0.98180    0.06298  15.588  < 2e-16 ***
## category_code_LT01_8_count  -0.04386    0.27906  -0.157    0.875    
## category_code_LT01_11_count  0.51127    0.11718   4.363 1.56e-05 ***
## category_code_LT01_12_count -0.08494    0.21621  -0.393    0.695    
## category_code_LT01_13_count  0.16411    0.24721   0.664    0.507    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6098 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.610098332631602 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0723 -0.7800 -0.0035  0.8932  4.2853 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01015    0.08873 112.818  < 2e-16 ***
## category_code_LT01_2_count   0.75406    0.08709   8.658  < 2e-16 ***
## category_code_LT01_5_count   0.97709    0.06330  15.437  < 2e-16 ***
## category_code_LT01_8_count  -0.05807    0.27856  -0.208    0.835    
## category_code_LT01_11_count  0.51267    0.11692   4.385 1.42e-05 ***
## category_code_LT01_12_count -0.09632    0.21659  -0.445    0.657    
## category_code_LT01_14_count  0.30477    0.33094   0.921    0.358    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6148, Adjusted R-squared:  0.6101 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.609516929851317 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0737 -0.7727 -0.0005  0.8904  4.2741 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00698    0.08873 112.781  < 2e-16 ***
## category_code_LT01_2_count   0.76094    0.08688   8.758  < 2e-16 ***
## category_code_LT01_5_count   0.98375    0.06295  15.628  < 2e-16 ***
## category_code_LT01_8_count  -0.05553    0.27877  -0.199    0.842    
## category_code_LT01_11_count  0.51360    0.11729   4.379 1.46e-05 ***
## category_code_LT01_12_count -0.08023    0.21639  -0.371    0.711    
## category_code_LT01_15_count  0.25923    0.76191   0.340    0.734    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6095 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.609452484708569 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0738 -0.7729  0.0064  0.8905  4.2722 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00728    0.08875 112.762  < 2e-16 ***
## category_code_LT01_2_count   0.76172    0.08710   8.745  < 2e-16 ***
## category_code_LT01_5_count   0.98345    0.06296  15.621  < 2e-16 ***
## category_code_LT01_8_count  -0.05664    0.27912  -0.203    0.839    
## category_code_LT01_11_count  0.51702    0.11695   4.421 1.21e-05 ***
## category_code_LT01_12_count -0.08210    0.21631  -0.380    0.704    
## category_code_LT01_16_count  0.22192    1.19100   0.186    0.852    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6095 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.610279035892712 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0684 -0.7850  0.0127  0.8984  4.2988 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00884    0.08870 112.839  < 2e-16 ***
## category_code_LT01_2_count   0.74821    0.08723   8.577  < 2e-16 ***
## category_code_LT01_5_count   0.97331    0.06318  15.406  < 2e-16 ***
## category_code_LT01_8_count  -0.05349    0.27866  -0.192    0.848    
## category_code_LT01_11_count  0.49411    0.11355   4.351 1.65e-05 ***
## category_code_LT01_13_count  0.16114    0.24702   0.652    0.515    
## category_code_LT01_14_count  0.29330    0.33012   0.888    0.375    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.615,  Adjusted R-squared:  0.6103 
## F-statistic: 130.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.609776204439835 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0700 -0.7855  0.0032  0.8926  4.2888 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00584    0.08870 112.810  < 2e-16 ***
## category_code_LT01_2_count   0.75445    0.08701   8.671  < 2e-16 ***
## category_code_LT01_5_count   0.98003    0.06279  15.608  < 2e-16 ***
## category_code_LT01_8_count  -0.04998    0.27880  -0.179    0.858    
## category_code_LT01_11_count  0.49630    0.11378   4.362 1.57e-05 ***
## category_code_LT01_13_count  0.16865    0.24764   0.681    0.496    
## category_code_LT01_15_count  0.30090    0.76262   0.395    0.693    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6098 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.609690494288763 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0701 -0.7787  0.0144  0.8953  4.2865 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00620    0.08872 112.789  < 2e-16 ***
## category_code_LT01_2_count   0.75539    0.08722   8.660  < 2e-16 ***
## category_code_LT01_5_count   0.97968    0.06280  15.600  < 2e-16 ***
## category_code_LT01_8_count  -0.05167    0.27913  -0.185    0.853    
## category_code_LT01_11_count  0.50012    0.11347   4.407 1.29e-05 ***
## category_code_LT01_13_count  0.16476    0.24739   0.666    0.506    
## category_code_LT01_16_count  0.26051    1.19134   0.219    0.827    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6097 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.610032840563647 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0704 -0.7637  0.0023  0.8884  4.2946 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00943    0.08872 112.817  < 2e-16 ***
## category_code_LT01_2_count   0.74994    0.08732   8.588  < 2e-16 ***
## category_code_LT01_5_count   0.97533    0.06314  15.446  < 2e-16 ***
## category_code_LT01_8_count  -0.06470    0.27836  -0.232    0.816    
## category_code_LT01_11_count  0.49699    0.11355   4.377 1.47e-05 ***
## category_code_LT01_14_count  0.29302    0.33025   0.887    0.375    
## category_code_LT01_15_count  0.25839    0.76104   0.340    0.734    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6147, Adjusted R-squared:   0.61 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.609989510930993 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0704 -0.7642  0.0045  0.8975  4.2943 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00987    0.08874 112.798  < 2e-16 ***
## category_code_LT01_2_count   0.74987    0.08763   8.557  < 2e-16 ***
## category_code_LT01_5_count   0.97480    0.06315  15.436  < 2e-16 ***
## category_code_LT01_8_count  -0.06687    0.27871  -0.240    0.810    
## category_code_LT01_11_count  0.50014    0.11328   4.415 1.24e-05 ***
## category_code_LT01_14_count  0.29962    0.33081   0.906    0.366    
## category_code_LT01_16_count  0.29372    1.19209   0.246    0.805    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6147, Adjusted R-squared:   0.61 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609441500743491 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0722 -0.7813  0.0010  0.8906  4.2822 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00679    0.08874 112.766  < 2e-16 ***
## category_code_LT01_2_count   0.75715    0.08733   8.670  < 2e-16 ***
## category_code_LT01_5_count   0.98176    0.06276  15.643  < 2e-16 ***
## category_code_LT01_8_count  -0.06303    0.27888  -0.226    0.821    
## category_code_LT01_11_count  0.50291    0.11347   4.432 1.15e-05 ***
## category_code_LT01_15_count  0.27502    0.76206   0.361    0.718    
## category_code_LT01_16_count  0.24600    1.19168   0.206    0.837    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6094 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.612891409882819 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0341 -0.7750  0.0188  0.9136  4.3735 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97607    0.09170 108.796  < 2e-16 ***
## category_code_LT01_2_count   0.72802    0.08778   8.293 1.07e-15 ***
## category_code_LT01_5_count   0.97122    0.06216  15.626  < 2e-16 ***
## category_code_LT01_9_count   0.39300    0.22999   1.709   0.0881 .  
## category_code_LT01_10_count  0.11650    0.11442   1.018   0.3091    
## category_code_LT01_11_count  0.49576    0.11684   4.243 2.64e-05 ***
## category_code_LT01_12_count -0.08785    0.21523  -0.408   0.6833    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6176, Adjusted R-squared:  0.6129 
## F-statistic: 132.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.613203056166949 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0310 -0.7871  0.0343  0.9257  4.3882 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97575    0.09166 108.839  < 2e-16 ***
## category_code_LT01_2_count   0.72110    0.08791   8.203 2.08e-15 ***
## category_code_LT01_5_count   0.96710    0.06194  15.613  < 2e-16 ***
## category_code_LT01_9_count   0.40555    0.23038   1.760    0.079 .  
## category_code_LT01_10_count  0.11184    0.11440   0.978    0.329    
## category_code_LT01_11_count  0.47704    0.11345   4.205 3.11e-05 ***
## category_code_LT01_13_count  0.18475    0.24637   0.750    0.454    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6179, Adjusted R-squared:  0.6132 
## F-statistic: 132.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.613014003066555 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0345 -0.7703  0.0306  0.9195  4.3816 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98079    0.09210 108.372  < 2e-16 ***
## category_code_LT01_2_count   0.72185    0.08801   8.202 2.08e-15 ***
## category_code_LT01_5_count   0.96491    0.06232  15.483  < 2e-16 ***
## category_code_LT01_9_count   0.38831    0.23017   1.687   0.0922 .  
## category_code_LT01_10_count  0.10114    0.11694   0.865   0.3875    
## category_code_LT01_11_count  0.48113    0.11322   4.250 2.56e-05 ***
## category_code_LT01_14_count  0.19138    0.33716   0.568   0.5706    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6177, Adjusted R-squared:  0.613 
## F-statistic: 132.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.612836625164534 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0330 -0.7693  0.0082  0.9222  4.3814 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97638    0.09172 108.773  < 2e-16 ***
## category_code_LT01_2_count   0.72408    0.08796   8.232 1.67e-15 ***
## category_code_LT01_5_count   0.96913    0.06192  15.651  < 2e-16 ***
## category_code_LT01_9_count   0.39654    0.23011   1.723   0.0855 .  
## category_code_LT01_10_count  0.11207    0.11477   0.977   0.3293    
## category_code_LT01_11_count  0.48136    0.11342   4.244 2.63e-05 ***
## category_code_LT01_15_count  0.23711    0.76094   0.312   0.7555    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6175, Adjusted R-squared:  0.6128 
## F-statistic: 132.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.612767259787679 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0325 -0.7702  0.0258  0.9192  4.3790 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97601    0.09173 108.752  < 2e-16 ***
## category_code_LT01_2_count   0.72540    0.08815   8.229 1.71e-15 ***
## category_code_LT01_5_count   0.96890    0.06193  15.644  < 2e-16 ***
## category_code_LT01_9_count   0.39366    0.23008   1.711   0.0877 .  
## category_code_LT01_10_count  0.11467    0.11445   1.002   0.3168    
## category_code_LT01_11_count  0.48407    0.11318   4.277 2.28e-05 ***
## category_code_LT01_16_count  0.11324    1.18544   0.096   0.9239    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6174, Adjusted R-squared:  0.6128 
## F-statistic: 132.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.612567559925689 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0575 -0.7899  0.0282  0.9067  4.3409 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00031    0.08839 113.140  < 2e-16 ***
## category_code_LT01_2_count   0.73203    0.08760   8.357 6.67e-16 ***
## category_code_LT01_5_count   0.96987    0.06223  15.586  < 2e-16 ***
## category_code_LT01_9_count   0.43208    0.22888   1.888   0.0596 .  
## category_code_LT01_11_count  0.49307    0.11715   4.209 3.05e-05 ***
## category_code_LT01_12_count -0.08304    0.21523  -0.386   0.6998    
## category_code_LT01_13_count  0.19486    0.24642   0.791   0.4295    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6172, Adjusted R-squared:  0.6126 
## F-statistic:   132 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.612570675029116 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0586 -0.7934  0.0237  0.8990  4.3409 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00388    0.08845 113.097  < 2e-16 ***
## category_code_LT01_2_count   0.73032    0.08780   8.318 8.88e-16 ***
## category_code_LT01_5_count   0.96642    0.06255  15.450  < 2e-16 ***
## category_code_LT01_9_count   0.40819    0.22901   1.782   0.0753 .  
## category_code_LT01_11_count  0.49716    0.11687   4.254 2.52e-05 ***
## category_code_LT01_12_count -0.09288    0.21573  -0.431   0.6670    
## category_code_LT01_14_count  0.26231    0.33067   0.793   0.4280    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6172, Adjusted R-squared:  0.6126 
## F-statistic:   132 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.61218869486427 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0595 -0.7905  0.0112  0.8975  4.3347 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00098    0.08843 113.099  < 2e-16 ***
## category_code_LT01_2_count   0.73469    0.08770   8.377 5.74e-16 ***
## category_code_LT01_5_count   0.97190    0.06221  15.623  < 2e-16 ***
## category_code_LT01_9_count   0.42295    0.22862   1.850   0.0649 .  
## category_code_LT01_11_count  0.49655    0.11725   4.235 2.73e-05 ***
## category_code_LT01_12_count -0.07818    0.21544  -0.363   0.7168    
## category_code_LT01_15_count  0.28923    0.75941   0.381   0.7035    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6169, Adjusted R-squared:  0.6122 
## F-statistic: 131.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.61208616758905 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0596 -0.7908  0.0149  0.9019  4.3306 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00123    0.08845 113.075  < 2e-16 ***
## category_code_LT01_2_count   0.73656    0.08786   8.384 5.46e-16 ***
## category_code_LT01_5_count   0.97170    0.06223  15.615  < 2e-16 ***
## category_code_LT01_9_count   0.42012    0.22869   1.837   0.0668 .  
## category_code_LT01_11_count  0.50035    0.11690   4.280 2.25e-05 ***
## category_code_LT01_12_count -0.08061    0.21537  -0.374   0.7083    
## category_code_LT01_16_count  0.14641    1.18595   0.123   0.9018    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6168, Adjusted R-squared:  0.6121 
## F-statistic: 131.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.612902558846595 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0543 -0.8058  0.0350  0.9253  4.3575 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00237    0.08841 113.141  < 2e-16 ***
## category_code_LT01_2_count   0.72305    0.08796   8.220 1.82e-15 ***
## category_code_LT01_5_count   0.96235    0.06238  15.428  < 2e-16 ***
## category_code_LT01_9_count   0.42068    0.22933   1.834   0.0672 .  
## category_code_LT01_11_count  0.47749    0.11353   4.206 3.09e-05 ***
## category_code_LT01_13_count  0.19181    0.24631   0.779   0.4365    
## category_code_LT01_14_count  0.24981    0.32975   0.758   0.4491    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6176, Adjusted R-squared:  0.6129 
## F-statistic: 132.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.612606058014336 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0554 -0.7892  0.0187  0.9211  4.3528 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99964    0.08837 113.152  < 2e-16 ***
## category_code_LT01_2_count   0.72662    0.08786   8.270 1.26e-15 ***
## category_code_LT01_5_count   0.96786    0.06199  15.614  < 2e-16 ***
## category_code_LT01_9_count   0.43554    0.22894   1.902   0.0577 .  
## category_code_LT01_11_count  0.47780    0.11379   4.199 3.18e-05 ***
## category_code_LT01_13_count  0.20069    0.24688   0.813   0.4167    
## category_code_LT01_15_count  0.33793    0.76008   0.445   0.6568    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6173, Adjusted R-squared:  0.6126 
## F-statistic:   132 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.612470396760255 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0555 -0.7895  0.0230  0.9162  4.3481 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99996    0.08840 113.125  < 2e-16 ***
## category_code_LT01_2_count   0.72875    0.08801   8.280 1.17e-15 ***
## category_code_LT01_5_count   0.96759    0.06201  15.604  < 2e-16 ***
## category_code_LT01_9_count   0.43184    0.22898   1.886   0.0599 .  
## category_code_LT01_11_count  0.48210    0.11347   4.249 2.57e-05 ***
## category_code_LT01_13_count  0.19529    0.24662   0.792   0.4288    
## category_code_LT01_16_count  0.19024    1.18616   0.160   0.8726    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6171, Adjusted R-squared:  0.6125 
## F-statistic: 131.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.612538525363553 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0565 -0.7926  0.0167  0.9118  4.3513 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00306    0.08844 113.103  < 2e-16 ***
## category_code_LT01_2_count   0.72573    0.08804   8.243 1.54e-15 ***
## category_code_LT01_5_count   0.96446    0.06236  15.467  < 2e-16 ***
## category_code_LT01_9_count   0.41165    0.22906   1.797   0.0729 .  
## category_code_LT01_11_count  0.48152    0.11351   4.242 2.65e-05 ***
## category_code_LT01_14_count  0.25021    0.32994   0.758   0.4486    
## category_code_LT01_15_count  0.28851    0.75873   0.380   0.7039    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6172, Adjusted R-squared:  0.6125 
## F-statistic:   132 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.612448774240915 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0565 -0.7930  0.0255  0.9032  4.3485 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00343    0.08847 113.078  < 2e-16 ***
## category_code_LT01_2_count   0.72688    0.08827   8.234 1.65e-15 ***
## category_code_LT01_5_count   0.96402    0.06238  15.454  < 2e-16 ***
## category_code_LT01_9_count   0.40823    0.22915   1.781   0.0755 .  
## category_code_LT01_11_count  0.48500    0.11324   4.283 2.22e-05 ***
## category_code_LT01_14_count  0.25595    0.33053   0.774   0.4391    
## category_code_LT01_16_count  0.20857    1.18742   0.176   0.8606    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6171, Adjusted R-squared:  0.6124 
## F-statistic: 131.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.612100934657905 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0577 -0.7902  0.0057  0.9035  4.3416 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00064    0.08843 113.085  < 2e-16 ***
## category_code_LT01_2_count   0.73154    0.08810   8.304 9.86e-16 ***
## category_code_LT01_5_count   0.96977    0.06198  15.646  < 2e-16 ***
## category_code_LT01_9_count   0.42285    0.22873   1.849   0.0651 .  
## category_code_LT01_11_count  0.48606    0.11346   4.284 2.21e-05 ***
## category_code_LT01_15_count  0.30268    0.75954   0.399   0.6904    
## category_code_LT01_16_count  0.17019    1.18657   0.143   0.8860    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6168, Adjusted R-squared:  0.6121 
## F-statistic: 131.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.610912755306223 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0393 -0.7656  0.0240  0.8951  4.3368 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97600    0.09193 108.518  < 2e-16 ***
## category_code_LT01_2_count   0.74572    0.08730   8.542  < 2e-16 ***
## category_code_LT01_5_count   0.97882    0.06213  15.755  < 2e-16 ***
## category_code_LT01_10_count  0.13769    0.11394   1.208    0.227    
## category_code_LT01_11_count  0.50538    0.11710   4.316 1.93e-05 ***
## category_code_LT01_12_count -0.09415    0.21577  -0.436    0.663    
## category_code_LT01_13_count  0.15752    0.24658   0.639    0.523    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6156, Adjusted R-squared:  0.6109 
## F-statistic: 131.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.610946439922333 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0430 -0.7694  0.0214  0.8985  4.3341 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98198    0.09235 108.088  < 2e-16 ***
## category_code_LT01_2_count   0.74413    0.08747   8.508  < 2e-16 ***
## category_code_LT01_5_count   0.97541    0.06249  15.608  < 2e-16 ***
## category_code_LT01_10_count  0.12306    0.11659   1.055    0.292    
## category_code_LT01_11_count  0.50839    0.11686   4.350 1.65e-05 ***
## category_code_LT01_12_count -0.10178    0.21619  -0.471    0.638    
## category_code_LT01_14_count  0.22717    0.33840   0.671    0.502    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6156, Adjusted R-squared:  0.6109 
## F-statistic: 131.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.610634764309909 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0408 -0.7660  0.0119  0.8881  4.3317 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97647    0.09198 108.464  < 2e-16 ***
## category_code_LT01_2_count   0.74795    0.08739   8.559  < 2e-16 ***
## category_code_LT01_5_count   0.98027    0.06212  15.781  < 2e-16 ***
## category_code_LT01_10_count  0.13762    0.11431   1.204    0.229    
## category_code_LT01_11_count  0.50851    0.11719   4.339 1.74e-05 ***
## category_code_LT01_12_count -0.09065    0.21598  -0.420    0.675    
## category_code_LT01_15_count  0.18261    0.76321   0.239    0.811    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6106 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.610602957853695 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0405 -0.7659  0.0196  0.8877  4.3310 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97631    0.09199 108.450  < 2e-16 ***
## category_code_LT01_2_count   0.74834    0.08763   8.540  < 2e-16 ***
## category_code_LT01_5_count   0.98002    0.06213  15.774  < 2e-16 ***
## category_code_LT01_10_count  0.13927    0.11402   1.221    0.222    
## category_code_LT01_11_count  0.51085    0.11688   4.371 1.51e-05 ***
## category_code_LT01_12_count -0.09209    0.21587  -0.427    0.670    
## category_code_LT01_16_count  0.15559    1.18854   0.131    0.896    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6153, Adjusted R-squared:  0.6106 
## F-statistic: 130.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.611089433007747 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0398 -0.7709  0.0348  0.9079  4.3463 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98136    0.09233 108.111  < 2e-16 ***
## category_code_LT01_2_count   0.73857    0.08758   8.433 3.79e-16 ***
## category_code_LT01_5_count   0.97170    0.06233  15.591  < 2e-16 ***
## category_code_LT01_10_count  0.12006    0.11661   1.030    0.304    
## category_code_LT01_11_count  0.48937    0.11353   4.311 1.97e-05 ***
## category_code_LT01_13_count  0.15635    0.24651   0.634    0.526    
## category_code_LT01_14_count  0.21713    0.33765   0.643    0.520    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6158, Adjusted R-squared:  0.6111 
## F-statistic: 131.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.610831534159635 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0381 -0.7658  0.0269  0.9012  4.3445 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97625    0.09195 108.491  < 2e-16 ***
## category_code_LT01_2_count   0.74186    0.08749   8.479 2.68e-16 ***
## category_code_LT01_5_count   0.97662    0.06190  15.776  < 2e-16 ***
## category_code_LT01_10_count  0.13346    0.11429   1.168    0.243    
## category_code_LT01_11_count  0.49024    0.11375   4.310 1.97e-05 ***
## category_code_LT01_13_count  0.16100    0.24710   0.652    0.515    
## category_code_LT01_15_count  0.22651    0.76409   0.296    0.767    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6155, Adjusted R-squared:  0.6108 
## F-statistic:   131 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.610783458735654 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0376 -0.7656  0.0305  0.8998  4.3437 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97606    0.09197 108.475  < 2e-16 ***
## category_code_LT01_2_count   0.74236    0.08774   8.461 3.07e-16 ***
## category_code_LT01_5_count   0.97628    0.06192  15.767  < 2e-16 ***
## category_code_LT01_10_count  0.13551    0.11399   1.189    0.235    
## category_code_LT01_11_count  0.49301    0.11347   4.345 1.69e-05 ***
## category_code_LT01_13_count  0.15800    0.24683   0.640    0.522    
## category_code_LT01_16_count  0.19618    1.18917   0.165    0.869    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6155, Adjusted R-squared:  0.6108 
## F-statistic:   131 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.610822594783957 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0414 -0.7714  0.0242  0.9019  4.3413 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98188    0.09238 108.058  < 2e-16 ***
## category_code_LT01_2_count   0.74072    0.08765   8.451 3.31e-16 ***
## category_code_LT01_5_count   0.97324    0.06231  15.619  < 2e-16 ***
## category_code_LT01_10_count  0.11987    0.11696   1.025    0.306    
## category_code_LT01_11_count  0.49281    0.11351   4.342 1.72e-05 ***
## category_code_LT01_14_count  0.21713    0.33777   0.643    0.521    
## category_code_LT01_15_count  0.19492    0.76251   0.256    0.798    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6155, Adjusted R-squared:  0.6108 
## F-statistic:   131 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.610797025834611 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0411 -0.7715  0.0324  0.9024  4.3415 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98190    0.09240 108.029  < 2e-16 ***
## category_code_LT01_2_count   0.74061    0.08796   8.420 4.18e-16 ***
## category_code_LT01_5_count   0.97279    0.06233  15.606  < 2e-16 ***
## category_code_LT01_10_count  0.12113    0.11675   1.037    0.300    
## category_code_LT01_11_count  0.49513    0.11327   4.371 1.51e-05 ***
## category_code_LT01_14_count  0.22120    0.33856   0.653    0.514    
## category_code_LT01_16_count  0.21659    1.19081   0.182    0.856    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.405 on 491 degrees of freedom
## Multiple R-squared:  0.6155, Adjusted R-squared:  0.6108 
## F-statistic:   131 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.610512485665526 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0392 -0.7661  0.0197  0.8963  4.3384 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97655    0.09202 108.419  < 2e-16 ***
## category_code_LT01_2_count   0.74468    0.08781   8.481 2.65e-16 ***
## category_code_LT01_5_count   0.97785    0.06190  15.797  < 2e-16 ***
## category_code_LT01_10_count  0.13537    0.11435   1.184    0.237    
## category_code_LT01_11_count  0.49643    0.11345   4.376 1.48e-05 ***
## category_code_LT01_15_count  0.19891    0.76342   0.261    0.795    
## category_code_LT01_16_count  0.17627    1.18946   0.148    0.882    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6152, Adjusted R-squared:  0.6105 
## F-statistic: 130.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.61041932755523 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0688 -0.7940  0.0044  0.8905  4.2958 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00900    0.08865 112.910  < 2e-16 ***
## category_code_LT01_2_count   0.74957    0.08727   8.589  < 2e-16 ***
## category_code_LT01_5_count   0.97367    0.06257  15.561  < 2e-16 ***
## category_code_LT01_11_count  0.50760    0.11715   4.333 1.78e-05 ***
## category_code_LT01_12_count -0.09999    0.21632  -0.462    0.644    
## category_code_LT01_13_count  0.16509    0.24663   0.669    0.504    
## category_code_LT01_14_count  0.30255    0.33077   0.915    0.361    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6151, Adjusted R-squared:  0.6104 
## F-statistic: 130.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.609869864779599 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0702 -0.7692 -0.0032  0.8926  4.2857 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00585    0.08865 112.875  < 2e-16 ***
## category_code_LT01_2_count   0.75591    0.08710   8.679  < 2e-16 ***
## category_code_LT01_5_count   0.98032    0.06220  15.761  < 2e-16 ***
## category_code_LT01_11_count  0.50789    0.11755   4.321 1.88e-05 ***
## category_code_LT01_12_count -0.08370    0.21609  -0.387    0.699    
## category_code_LT01_13_count  0.17201    0.24727   0.696    0.487    
## category_code_LT01_15_count  0.28943    0.76292   0.379    0.705    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6146, Adjusted R-squared:  0.6099 
## F-statistic: 130.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.609788639261177 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0703 -0.7689 -0.0028  0.8998  4.2833 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00618    0.08866 112.857  < 2e-16 ***
## category_code_LT01_2_count   0.75691    0.08732   8.669  < 2e-16 ***
## category_code_LT01_5_count   0.97998    0.06222  15.750  < 2e-16 ***
## category_code_LT01_11_count  0.51184    0.11717   4.368 1.53e-05 ***
## category_code_LT01_12_count -0.08580    0.21601  -0.397    0.691    
## category_code_LT01_13_count  0.16831    0.24704   0.681    0.496    
## category_code_LT01_16_count  0.24295    1.18996   0.204    0.838    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6098 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.610145318392828 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0703 -0.7774 -0.0086  0.8861  4.2915 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00946    0.08867 112.879  < 2e-16 ***
## category_code_LT01_2_count   0.75140    0.08739   8.598  < 2e-16 ***
## category_code_LT01_5_count   0.97523    0.06256  15.589  < 2e-16 ***
## category_code_LT01_11_count  0.51026    0.11725   4.352 1.64e-05 ***
## category_code_LT01_12_count -0.09578    0.21652  -0.442    0.658    
## category_code_LT01_14_count  0.30171    0.33094   0.912    0.362    
## category_code_LT01_15_count  0.24391    0.76133   0.320    0.749    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6149, Adjusted R-squared:  0.6101 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.610105580946325 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0703 -0.7773  0.0024  0.8884  4.2911 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00986    0.08869 112.865  < 2e-16 ***
## category_code_LT01_2_count   0.75140    0.08770   8.568  < 2e-16 ***
## category_code_LT01_5_count   0.97470    0.06258  15.574  < 2e-16 ***
## category_code_LT01_11_count  0.51349    0.11691   4.392 1.37e-05 ***
## category_code_LT01_12_count -0.09768    0.21641  -0.451    0.652    
## category_code_LT01_14_count  0.30803    0.33144   0.929    0.353    
## category_code_LT01_16_count  0.27297    1.19042   0.229    0.819    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6148, Adjusted R-squared:  0.6101 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609513783357912 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0719 -0.7690 -0.0147  0.8909  4.2790 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00663    0.08869 112.826  < 2e-16 ***
## category_code_LT01_2_count   0.75875    0.08745   8.676  < 2e-16 ***
## category_code_LT01_5_count   0.98157    0.06220  15.780  < 2e-16 ***
## category_code_LT01_11_count  0.51434    0.11727   4.386 1.41e-05 ***
## category_code_LT01_12_count -0.08147    0.21621  -0.377    0.706    
## category_code_LT01_15_count  0.26216    0.76235   0.344    0.731    
## category_code_LT01_16_count  0.22494    1.19020   0.189    0.850    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6095 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.610363331818727 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0665 -0.7756  0.0045  0.8904  4.3062 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00816    0.08864 112.911  < 2e-16 ***
## category_code_LT01_2_count   0.74494    0.08754   8.510  < 2e-16 ***
## category_code_LT01_5_count   0.97158    0.06239  15.574  < 2e-16 ***
## category_code_LT01_11_count  0.49099    0.11386   4.312 1.95e-05 ***
## category_code_LT01_13_count  0.16951    0.24711   0.686    0.493    
## category_code_LT01_14_count  0.29002    0.33006   0.879    0.380    
## category_code_LT01_15_count  0.28827    0.76211   0.378    0.705    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6151, Adjusted R-squared:  0.6104 
## F-statistic: 130.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.610304243414326 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0665 -0.7760  0.0160  0.8961  4.3055 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00861    0.08865 112.894  < 2e-16 ***
## category_code_LT01_2_count   0.74508    0.08785   8.481 2.63e-16 ***
## category_code_LT01_5_count   0.97095    0.06241  15.557  < 2e-16 ***
## category_code_LT01_11_count  0.49460    0.11355   4.356 1.62e-05 ***
## category_code_LT01_13_count  0.16636    0.24686   0.674    0.501    
## category_code_LT01_14_count  0.29710    0.33060   0.899    0.369    
## category_code_LT01_16_count  0.31197    1.19104   0.262    0.793    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.615,  Adjusted R-squared:  0.6103 
## F-statistic: 130.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609791156768943 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0683 -0.7799  0.0018  0.8912  4.2946 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00557    0.08865 112.864  < 2e-16 ***
## category_code_LT01_2_count   0.75177    0.08759   8.583  < 2e-16 ***
## category_code_LT01_5_count   0.97794    0.06198  15.777  < 2e-16 ***
## category_code_LT01_11_count  0.49674    0.11378   4.366 1.55e-05 ***
## category_code_LT01_13_count  0.17346    0.24752   0.701    0.484    
## category_code_LT01_15_count  0.30615    0.76316   0.401    0.688    
## category_code_LT01_16_count  0.26880    1.19075   0.226    0.821    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6098 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_2_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.610038253404727 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0681 -0.7596  0.0021  0.8892  4.3011 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00908    0.08868 112.865  < 2e-16 ***
## category_code_LT01_2_count   0.74698    0.08795   8.493 2.41e-16 ***
## category_code_LT01_5_count   0.97266    0.06239  15.589  < 2e-16 ***
## category_code_LT01_11_count  0.49764    0.11355   4.383 1.43e-05 ***
## category_code_LT01_14_count  0.29629    0.33074   0.896    0.371    
## category_code_LT01_15_count  0.26261    0.76145   0.345    0.730    
## category_code_LT01_16_count  0.29384    1.19122   0.247    0.805    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6147, Adjusted R-squared:   0.61 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count 0.6313171063544 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9857 -0.7511  0.0468  0.9200  3.4749 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97623    0.08631 115.590  < 2e-16 ***
## category_code_LT01_3_count  0.32970    0.11172   2.951  0.00332 ** 
## category_code_LT01_4_count  0.74209    0.09008   8.238  1.6e-15 ***
## category_code_LT01_5_count  0.90104    0.06219  14.488  < 2e-16 ***
## category_code_LT01_6_count  0.45189    0.14897   3.033  0.00255 ** 
## category_code_LT01_7_count  0.49602    0.15181   3.267  0.00116 ** 
## category_code_LT01_8_count -0.20677    0.27102  -0.763  0.44589    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6358, Adjusted R-squared:  0.6313 
## F-statistic: 142.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count 0.632432615550202 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9723 -0.7485  0.0414  0.9309  3.5253 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97116    0.08617 115.711  < 2e-16 ***
## category_code_LT01_3_count  0.30442    0.11277   2.699  0.00719 ** 
## category_code_LT01_4_count  0.73584    0.09008   8.169 2.65e-15 ***
## category_code_LT01_5_count  0.88904    0.06157  14.439  < 2e-16 ***
## category_code_LT01_6_count  0.43610    0.14887   2.929  0.00355 ** 
## category_code_LT01_7_count  0.47007    0.15231   3.086  0.00214 ** 
## category_code_LT01_9_count  0.32375    0.22481   1.440  0.15048    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.365 on 491 degrees of freedom
## Multiple R-squared:  0.6369, Adjusted R-squared:  0.6324 
## F-statistic: 143.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count 0.630934310987496 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9731 -0.7524  0.0166  0.9352  3.4608 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96815    0.08941 111.482  < 2e-16 ***
## category_code_LT01_3_count   0.32332    0.11334   2.853  0.00452 ** 
## category_code_LT01_4_count   0.74346    0.09014   8.247 1.49e-15 ***
## category_code_LT01_5_count   0.89455    0.06160  14.523  < 2e-16 ***
## category_code_LT01_6_count   0.44164    0.15067   2.931  0.00353 ** 
## category_code_LT01_7_count   0.48932    0.15228   3.213  0.00140 ** 
## category_code_LT01_10_count  0.03062    0.11398   0.269  0.78834    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6354, Adjusted R-squared:  0.6309 
## F-statistic: 142.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count 0.634907531644201 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9846 -0.7495  0.0248  0.9038  3.4724 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98023    0.08589 116.199  < 2e-16 ***
## category_code_LT01_3_count   0.26391    0.11456   2.304  0.02166 *  
## category_code_LT01_4_count   0.65876    0.09666   6.815 2.77e-11 ***
## category_code_LT01_5_count   0.89380    0.06126  14.591  < 2e-16 ***
## category_code_LT01_6_count   0.38869    0.15030   2.586  0.00999 ** 
## category_code_LT01_7_count   0.40001    0.15614   2.562  0.01071 *  
## category_code_LT01_11_count  0.27250    0.11709   2.327  0.02035 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.361 on 491 degrees of freedom
## Multiple R-squared:  0.6393, Adjusted R-squared:  0.6349 
## F-statistic:   145 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count 0.63095726944896 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9779 -0.7390  0.0211  0.9280  3.4838 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97423    0.08632 115.552  < 2e-16 ***
## category_code_LT01_3_count   0.32586    0.11204   2.908  0.00380 ** 
## category_code_LT01_4_count   0.73973    0.09068   8.158 2.88e-15 ***
## category_code_LT01_5_count   0.89270    0.06178  14.449  < 2e-16 ***
## category_code_LT01_6_count   0.44192    0.15005   2.945  0.00338 ** 
## category_code_LT01_7_count   0.49190    0.15183   3.240  0.00128 ** 
## category_code_LT01_12_count  0.06540    0.20408   0.320  0.74875    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6354, Adjusted R-squared:  0.631 
## F-statistic: 142.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count 0.630901955751937 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9789 -0.7352  0.0136  0.9324  3.4797 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97433    0.08632 115.545  < 2e-16 ***
## category_code_LT01_3_count   0.32809    0.11179   2.935  0.00349 ** 
## category_code_LT01_4_count   0.74154    0.09050   8.193 2.22e-15 ***
## category_code_LT01_5_count   0.89407    0.06160  14.513  < 2e-16 ***
## category_code_LT01_6_count   0.44807    0.14897   3.008  0.00277 ** 
## category_code_LT01_7_count   0.48939    0.15291   3.200  0.00146 ** 
## category_code_LT01_13_count  0.04129    0.24203   0.171  0.86461    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6354, Adjusted R-squared:  0.6309 
## F-statistic: 142.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count 0.631157082663155 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9780 -0.7377  0.0393  0.9234  3.4805 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97617    0.08634 115.544  < 2e-16 ***
## category_code_LT01_3_count   0.33066    0.11180   2.958  0.00325 ** 
## category_code_LT01_4_count   0.73162    0.09201   7.952 1.27e-14 ***
## category_code_LT01_5_count   0.89009    0.06195  14.367  < 2e-16 ***
## category_code_LT01_6_count   0.45536    0.14943   3.047  0.00243 ** 
## category_code_LT01_7_count   0.48564    0.15219   3.191  0.00151 ** 
## category_code_LT01_14_count  0.19770    0.32556   0.607  0.54397    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6356, Adjusted R-squared:  0.6312 
## F-statistic: 142.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count 0.630880610519418 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9791 -0.7354  0.0114  0.9397  3.4784 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97440    0.08633 115.539  < 2e-16 ***
## category_code_LT01_3_count   0.32876    0.11270   2.917  0.00369 ** 
## category_code_LT01_4_count   0.74310    0.09032   8.227 1.73e-15 ***
## category_code_LT01_5_count   0.89423    0.06162  14.513  < 2e-16 ***
## category_code_LT01_6_count   0.44790    0.14908   3.004  0.00280 ** 
## category_code_LT01_7_count   0.49235    0.15192   3.241  0.00127 ** 
## category_code_LT01_15_count -0.01990    0.74700  -0.027  0.97875    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6353, Adjusted R-squared:  0.6309 
## F-statistic: 142.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_16_count 0.631509257578926 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9783 -0.7394  0.0196  0.9407  3.5037 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97461    0.08625 115.645  < 2e-16 ***
## category_code_LT01_3_count   0.31456    0.11270   2.791  0.00546 ** 
## category_code_LT01_4_count   0.74212    0.09006   8.240 1.57e-15 ***
## category_code_LT01_5_count   0.89271    0.06156  14.501  < 2e-16 ***
## category_code_LT01_6_count   0.45825    0.14928   3.070  0.00226 ** 
## category_code_LT01_7_count   0.49282    0.15170   3.249  0.00124 ** 
## category_code_LT01_16_count  1.06222    1.16011   0.916  0.36032    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.636,  Adjusted R-squared:  0.6315 
## F-statistic:   143 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count 0.625685477923506 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9843 -0.7620  0.0403  0.9049  3.4986 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.97242    0.08699 114.636  < 2e-16 ***
## category_code_LT01_3_count  0.31861    0.11373   2.801  0.00529 ** 
## category_code_LT01_4_count  0.82632    0.08592   9.618  < 2e-16 ***
## category_code_LT01_5_count  0.90450    0.06270  14.426  < 2e-16 ***
## category_code_LT01_6_count  0.44336    0.15032   2.950  0.00333 ** 
## category_code_LT01_8_count -0.19366    0.27307  -0.709  0.47854    
## category_code_LT01_9_count  0.39927    0.22577   1.768  0.07760 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6257 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count 0.623511273229027 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9808 -0.7536 -0.0113  0.9104  3.4044 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96405    0.09032 110.323  < 2e-16 ***
## category_code_LT01_3_count   0.33900    0.11439   2.963  0.00319 ** 
## category_code_LT01_4_count   0.84037    0.08579   9.796  < 2e-16 ***
## category_code_LT01_5_count   0.91158    0.06278  14.521  < 2e-16 ***
## category_code_LT01_6_count   0.44579    0.15227   2.928  0.00357 ** 
## category_code_LT01_8_count  -0.18174    0.27378  -0.664  0.50712    
## category_code_LT01_10_count  0.06008    0.11479   0.523  0.60094    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6235 
## F-statistic: 138.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count 0.630264975463631 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9970 -0.7526  0.0552  0.8988  3.4547 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98341    0.08646 115.467  < 2e-16 ***
## category_code_LT01_3_count   0.26228    0.11532   2.274  0.02337 *  
## category_code_LT01_4_count   0.71013    0.09522   7.458 4.02e-13 ***
## category_code_LT01_5_count   0.90700    0.06222  14.578  < 2e-16 ***
## category_code_LT01_6_count   0.38058    0.15132   2.515  0.01222 *  
## category_code_LT01_8_count  -0.15243    0.27143  -0.562  0.57466    
## category_code_LT01_11_count  0.34671    0.11401   3.041  0.00248 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6347, Adjusted R-squared:  0.6303 
## F-statistic: 142.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count 0.62340972209746 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9913 -0.7630  0.0117  0.9081  3.4594 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97613    0.08723 114.367  < 2e-16 ***
## category_code_LT01_3_count   0.34616    0.11303   3.062  0.00232 ** 
## category_code_LT01_4_count   0.83663    0.08644   9.679  < 2e-16 ***
## category_code_LT01_5_count   0.90933    0.06296  14.444  < 2e-16 ***
## category_code_LT01_6_count   0.45096    0.15164   2.974  0.00309 ** 
## category_code_LT01_8_count  -0.18292    0.27392  -0.668  0.50459    
## category_code_LT01_12_count  0.07757    0.20624   0.376  0.70700    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.628,  Adjusted R-squared:  0.6234 
## F-statistic: 138.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count 0.623502260025409 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9916 -0.7632  0.0181  0.9001  3.4588 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97600    0.08722 114.378  < 2e-16 ***
## category_code_LT01_3_count   0.34785    0.11277   3.085  0.00215 ** 
## category_code_LT01_4_count   0.83449    0.08661   9.636  < 2e-16 ***
## category_code_LT01_5_count   0.91000    0.06281  14.489  < 2e-16 ***
## category_code_LT01_6_count   0.45852    0.15054   3.046  0.00244 ** 
## category_code_LT01_8_count  -0.17162    0.27421  -0.626  0.53170    
## category_code_LT01_13_count  0.12449    0.24312   0.512  0.60886    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.628,  Adjusted R-squared:  0.6235 
## F-statistic: 138.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count 0.623855025976649 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9911 -0.7471  0.0186  0.9074  3.4613 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97883    0.08723 114.403  < 2e-16 ***
## category_code_LT01_3_count   0.35202    0.11274   3.122  0.00190 ** 
## category_code_LT01_4_count   0.82268    0.08829   9.318  < 2e-16 ***
## category_code_LT01_5_count   0.90514    0.06313  14.337  < 2e-16 ***
## category_code_LT01_6_count   0.46851    0.15099   3.103  0.00203 ** 
## category_code_LT01_8_count  -0.18407    0.27367  -0.673  0.50152    
## category_code_LT01_14_count  0.27881    0.32792   0.850  0.39561    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6284, Adjusted R-squared:  0.6239 
## F-statistic: 138.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count 0.623313800737415 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9925 -0.7532  0.0151  0.9121  3.4576 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97622    0.08724 114.350  < 2e-16 ***
## category_code_LT01_3_count   0.35099    0.11367   3.088  0.00213 ** 
## category_code_LT01_4_count   0.84121    0.08595   9.787  < 2e-16 ***
## category_code_LT01_5_count   0.91087    0.06281  14.501  < 2e-16 ***
## category_code_LT01_6_count   0.45856    0.15069   3.043  0.00247 ** 
## category_code_LT01_8_count  -0.17947    0.27383  -0.655  0.51251    
## category_code_LT01_15_count -0.09656    0.75422  -0.128  0.89818    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6279, Adjusted R-squared:  0.6233 
## F-statistic: 138.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_16_count 0.623968169859069 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9922 -0.7528  0.0065  0.9050  3.4650 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97664    0.08716 114.459  < 2e-16 ***
## category_code_LT01_3_count   0.33501    0.11369   2.947  0.00336 ** 
## category_code_LT01_4_count   0.83979    0.08574   9.795  < 2e-16 ***
## category_code_LT01_5_count   0.90994    0.06274  14.502  < 2e-16 ***
## category_code_LT01_6_count   0.46890    0.15091   3.107  0.00200 ** 
## category_code_LT01_8_count  -0.19272    0.27394  -0.704  0.48207    
## category_code_LT01_16_count  1.09504    1.17343   0.933  0.35118    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.624 
## F-statistic: 138.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count 0.625394445419011 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9704 -0.7628  0.0272  0.9266  3.4773 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96265    0.09007 110.614  < 2e-16 ***
## category_code_LT01_3_count   0.31141    0.11515   2.704  0.00708 ** 
## category_code_LT01_4_count   0.82675    0.08595   9.619  < 2e-16 ***
## category_code_LT01_5_count   0.89858    0.06210  14.471  < 2e-16 ***
## category_code_LT01_6_count   0.43186    0.15192   2.843  0.00466 ** 
## category_code_LT01_9_count   0.38701    0.22683   1.706  0.08860 .  
## category_code_LT01_10_count  0.04003    0.11503   0.348  0.72799    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6254 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count 0.631937045307109 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9840 -0.7678  0.0607  0.9137  3.4722 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97829    0.08627 115.666  < 2e-16 ***
## category_code_LT01_3_count   0.23573    0.11608   2.031  0.04281 *  
## category_code_LT01_4_count   0.70046    0.09516   7.361 7.77e-13 ***
## category_code_LT01_5_count   0.89569    0.06155  14.553  < 2e-16 ***
## category_code_LT01_6_count   0.36606    0.15100   2.424  0.01570 *  
## category_code_LT01_9_count   0.35772    0.22413   1.596  0.11112    
## category_code_LT01_11_count  0.33876    0.11387   2.975  0.00307 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.366 on 491 degrees of freedom
## Multiple R-squared:  0.6364, Adjusted R-squared:  0.6319 
## F-statistic: 143.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count 0.625395048855176 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9768 -0.7601  0.0330  0.9230  3.5072 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97056    0.08700 114.609  < 2e-16 ***
## category_code_LT01_3_count   0.31483    0.11404   2.761  0.00598 ** 
## category_code_LT01_4_count   0.82299    0.08658   9.506  < 2e-16 ***
## category_code_LT01_5_count   0.89643    0.06229  14.392  < 2e-16 ***
## category_code_LT01_6_count   0.43323    0.15139   2.862  0.00439 ** 
## category_code_LT01_9_count   0.39431    0.22577   1.747  0.08134 .  
## category_code_LT01_12_count  0.07178    0.20560   0.349  0.72713    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6254 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count 0.625631552184243 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9769 -0.7599  0.0366  0.9171  3.5066 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97034    0.08697 114.642  < 2e-16 ***
## category_code_LT01_3_count   0.31531    0.11378   2.771  0.00580 ** 
## category_code_LT01_4_count   0.81850    0.08680   9.429  < 2e-16 ***
## category_code_LT01_5_count   0.89694    0.06209  14.445  < 2e-16 ***
## category_code_LT01_6_count   0.44041    0.15024   2.931  0.00353 ** 
## category_code_LT01_9_count   0.40362    0.22610   1.785  0.07486 .  
## category_code_LT01_13_count  0.15940    0.24247   0.657  0.51124    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6256 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count 0.62567561870785 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9770 -0.7625  0.0321  0.9185  3.4939 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97292    0.08702 114.610  < 2e-16 ***
## category_code_LT01_3_count   0.32092    0.11382   2.819  0.00500 ** 
## category_code_LT01_4_count   0.81234    0.08831   9.199  < 2e-16 ***
## category_code_LT01_5_count   0.89336    0.06244  14.307  < 2e-16 ***
## category_code_LT01_6_count   0.44883    0.15080   2.976  0.00306 ** 
## category_code_LT01_9_count   0.38176    0.22643   1.686  0.09243 .  
## category_code_LT01_14_count  0.22971    0.32816   0.700  0.48425    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6257 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count 0.625305249431648 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9781 -0.7580  0.0285  0.9211  3.5004 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97072    0.08701 114.595  < 2e-16 ***
## category_code_LT01_3_count   0.31857    0.11476   2.776  0.00572 ** 
## category_code_LT01_4_count   0.82696    0.08612   9.603  < 2e-16 ***
## category_code_LT01_5_count   0.89807    0.06211  14.458  < 2e-16 ***
## category_code_LT01_6_count   0.44001    0.15043   2.925  0.00360 ** 
## category_code_LT01_9_count   0.39407    0.22596   1.744  0.08179 .  
## category_code_LT01_15_count -0.04876    0.75278  -0.065  0.94838    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6253 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_16_count 0.625846577862425 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9775 -0.7574  0.0286  0.9304  3.5240 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97101    0.08694 114.685  < 2e-16 ***
## category_code_LT01_3_count   0.30521    0.11464   2.662  0.00801 ** 
## category_code_LT01_4_count   0.82614    0.08590   9.618  < 2e-16 ***
## category_code_LT01_5_count   0.89683    0.06207  14.449  < 2e-16 ***
## category_code_LT01_6_count   0.44962    0.15066   2.984  0.00298 ** 
## category_code_LT01_9_count   0.38854    0.22574   1.721  0.08585 .  
## category_code_LT01_16_count  0.98868    1.16958   0.845  0.39834    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6304, Adjusted R-squared:  0.6258 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count 0.630236723397719 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9802 -0.7457  0.0225  0.9162  3.4075 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96985    0.08951 111.378  < 2e-16 ***
## category_code_LT01_3_count   0.25049    0.11689   2.143  0.03261 *  
## category_code_LT01_4_count   0.70917    0.09522   7.448  4.3e-13 ***
## category_code_LT01_5_count   0.90233    0.06157  14.656  < 2e-16 ***
## category_code_LT01_6_count   0.36497    0.15291   2.387  0.01737 *  
## category_code_LT01_10_count  0.05996    0.11375   0.527  0.59837    
## category_code_LT01_11_count  0.34899    0.11395   3.063  0.00232 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6347, Adjusted R-squared:  0.6302 
## F-statistic: 142.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count 0.623265230706741 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9740 -0.7522 -0.0034  0.9263  3.4150 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96262    0.09032 110.300  < 2e-16 ***
## category_code_LT01_3_count   0.33525    0.11467   2.924  0.00362 ** 
## category_code_LT01_4_count   0.83687    0.08645   9.680  < 2e-16 ***
## category_code_LT01_5_count   0.90382    0.06234  14.498  < 2e-16 ***
## category_code_LT01_6_count   0.43612    0.15328   2.845  0.00462 ** 
## category_code_LT01_10_count  0.05827    0.11483   0.507  0.61211    
## category_code_LT01_12_count  0.07134    0.20621   0.346  0.72951    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6278, Adjusted R-squared:  0.6233 
## F-statistic:   138 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count 0.623391792407164 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9747 -0.7523 -0.0055  0.9141  3.4151 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96278    0.09031 110.321  < 2e-16 ***
## category_code_LT01_3_count   0.33692    0.11441   2.945  0.00339 ** 
## category_code_LT01_4_count   0.83416    0.08662   9.630  < 2e-16 ***
## category_code_LT01_5_count   0.90467    0.06215  14.556  < 2e-16 ***
## category_code_LT01_6_count   0.44361    0.15222   2.914  0.00373 ** 
## category_code_LT01_10_count  0.05714    0.11485   0.498  0.61902    
## category_code_LT01_13_count  0.12959    0.24286   0.534  0.59385    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6279, Adjusted R-squared:  0.6234 
## F-statistic: 138.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count 0.623587355064072 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9779 -0.7435 -0.0018  0.9169  3.4350 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96918    0.09072 109.894  < 2e-16 ***
## category_code_LT01_3_count   0.34399    0.11467   3.000  0.00284 ** 
## category_code_LT01_4_count   0.82463    0.08845   9.323  < 2e-16 ***
## category_code_LT01_5_count   0.89996    0.06258  14.382  < 2e-16 ***
## category_code_LT01_6_count   0.45601    0.15330   2.975  0.00308 ** 
## category_code_LT01_10_count  0.03795    0.11829   0.321  0.74849    
## category_code_LT01_14_count  0.24841    0.33805   0.735  0.46279    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6236 
## F-statistic: 138.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count 0.623193418146389 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9747 -0.7519 -0.0118  0.9284  3.4117 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96232    0.09036 110.255  < 2e-16 ***
## category_code_LT01_3_count   0.34005    0.11520   2.952  0.00331 ** 
## category_code_LT01_4_count   0.84129    0.08596   9.787  < 2e-16 ***
## category_code_LT01_5_count   0.90527    0.06217  14.562  < 2e-16 ***
## category_code_LT01_6_count   0.44308    0.15231   2.909  0.00379 ** 
## category_code_LT01_10_count  0.06004    0.11500   0.522  0.60186    
## category_code_LT01_15_count -0.12205    0.75549  -0.162  0.87173    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6277, Adjusted R-squared:  0.6232 
## F-statistic:   138 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_16_count 0.623764622344067 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9752 -0.7513 -0.0143  0.9234  3.4352 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96369    0.09027 110.376  < 2e-16 ***
## category_code_LT01_3_count   0.32519    0.11525   2.821  0.00497 ** 
## category_code_LT01_4_count   0.83978    0.08576   9.792  < 2e-16 ***
## category_code_LT01_5_count   0.90402    0.06212  14.553  < 2e-16 ***
## category_code_LT01_6_count   0.45334    0.15264   2.970  0.00312 ** 
## category_code_LT01_10_count  0.05495    0.11483   0.479  0.63247    
## category_code_LT01_16_count  1.03051    1.17318   0.878  0.38016    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6283, Adjusted R-squared:  0.6238 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count 0.630151935948373 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9940 -0.7513  0.0352  0.9070  3.4589 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98261    0.08645 115.469  < 2e-16 ***
## category_code_LT01_3_count   0.26106    0.11530   2.264  0.02400 *  
## category_code_LT01_4_count   0.70937    0.09523   7.449 4.26e-13 ***
## category_code_LT01_5_count   0.90391    0.06176  14.635  < 2e-16 ***
## category_code_LT01_6_count   0.38205    0.15171   2.518  0.01211 *  
## category_code_LT01_11_count  0.36058    0.11758   3.067  0.00228 ** 
## category_code_LT01_12_count -0.08566    0.21076  -0.406  0.68459    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6346, Adjusted R-squared:  0.6302 
## F-statistic: 142.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count 0.630132702331056 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9915 -0.7417  0.0337  0.9002  3.4624 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98187    0.08645 115.466  < 2e-16 ***
## category_code_LT01_3_count   0.26040    0.11530   2.258  0.02436 *  
## category_code_LT01_4_count   0.70598    0.09568   7.379 6.88e-13 ***
## category_code_LT01_5_count   0.90134    0.06159  14.634  < 2e-16 ***
## category_code_LT01_6_count   0.37822    0.15125   2.501  0.01272 *  
## category_code_LT01_11_count  0.34630    0.11417   3.033  0.00255 ** 
## category_code_LT01_13_count  0.09006    0.24099   0.374  0.70878    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6346, Adjusted R-squared:  0.6301 
## F-statistic: 142.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count 0.630377062738799 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9907 -0.7403  0.0408  0.8896  3.4650 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98398    0.08646 115.474  < 2e-16 ***
## category_code_LT01_3_count   0.26397    0.11537   2.288  0.02255 *  
## category_code_LT01_4_count   0.69678    0.09699   7.184 2.53e-12 ***
## category_code_LT01_5_count   0.89710    0.06196  14.479  < 2e-16 ***
## category_code_LT01_6_count   0.38640    0.15179   2.546  0.01121 *  
## category_code_LT01_11_count  0.34464    0.11410   3.021  0.00265 ** 
## category_code_LT01_14_count  0.22180    0.32548   0.681  0.49592    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6348, Adjusted R-squared:  0.6304 
## F-statistic: 142.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count 0.630062819287676 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9917 -0.7455  0.0366  0.9135  3.4622 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98195    0.08646 115.455  < 2e-16 ***
## category_code_LT01_3_count   0.26358    0.11610   2.270   0.0236 *  
## category_code_LT01_4_count   0.71024    0.09531   7.452 4.19e-13 ***
## category_code_LT01_5_count   0.90154    0.06161  14.634  < 2e-16 ***
## category_code_LT01_6_count   0.37816    0.15132   2.499   0.0128 *  
## category_code_LT01_11_count  0.34949    0.11402   3.065   0.0023 ** 
## category_code_LT01_15_count -0.16189    0.74769  -0.217   0.8287    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:  0.6301 
## F-statistic: 142.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_16_count 0.630559138090662 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9913 -0.7482  0.0336  0.9168  3.4630 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98225    0.08640 115.540  < 2e-16 ***
## category_code_LT01_3_count   0.24849    0.11614   2.140  0.03289 *  
## category_code_LT01_4_count   0.70953    0.09518   7.455  4.1e-13 ***
## category_code_LT01_5_count   0.90052    0.06156  14.628  < 2e-16 ***
## category_code_LT01_6_count   0.38715    0.15161   2.554  0.01096 *  
## category_code_LT01_11_count  0.34676    0.11393   3.044  0.00246 ** 
## category_code_LT01_16_count  0.97664    1.16187   0.841  0.40099    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.635,  Adjusted R-squared:  0.6306 
## F-statistic: 142.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count 0.623290299970919 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9848 -0.7510  0.0120  0.9185  3.4687 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97427    0.08721 114.369  < 2e-16 ***
## category_code_LT01_3_count   0.34385    0.11306   3.041  0.00248 ** 
## category_code_LT01_4_count   0.83074    0.08722   9.525  < 2e-16 ***
## category_code_LT01_5_count   0.90257    0.06235  14.476  < 2e-16 ***
## category_code_LT01_6_count   0.44885    0.15160   2.961  0.00322 ** 
## category_code_LT01_12_count  0.07001    0.20626   0.339  0.73443    
## category_code_LT01_13_count  0.13083    0.24289   0.539  0.59038    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6278, Adjusted R-squared:  0.6233 
## F-statistic: 138.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count 0.623568946370718 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9842 -0.7480  0.0018  0.9278  3.4712 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97693    0.08723 114.377  < 2e-16 ***
## category_code_LT01_3_count   0.34833    0.11307   3.081  0.00218 ** 
## category_code_LT01_4_count   0.82066    0.08874   9.248  < 2e-16 ***
## category_code_LT01_5_count   0.89790    0.06268  14.326  < 2e-16 ***
## category_code_LT01_6_count   0.45912    0.15220   3.017  0.00269 ** 
## category_code_LT01_12_count  0.05813    0.20695   0.281  0.77891    
## category_code_LT01_14_count  0.26630    0.32935   0.809  0.41915    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6236 
## F-statistic: 138.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count 0.623079193509732 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9853 -0.7526  0.0095  0.9315  3.4679 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97444    0.08724 114.335  < 2e-16 ***
## category_code_LT01_3_count   0.34682    0.11401   3.042  0.00248 ** 
## category_code_LT01_4_count   0.83761    0.08663   9.669  < 2e-16 ***
## category_code_LT01_5_count   0.90318    0.06237  14.481  < 2e-16 ***
## category_code_LT01_6_count   0.44842    0.15177   2.955  0.00328 ** 
## category_code_LT01_12_count  0.07256    0.20632   0.352  0.72523    
## category_code_LT01_15_count -0.09233    0.75476  -0.122  0.90268    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6276, Adjusted R-squared:  0.6231 
## F-statistic: 137.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_16_count 0.623686052669408 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9847 -0.7615  0.0026  0.9228  3.4735 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97473    0.08716 114.435  < 2e-16 ***
## category_code_LT01_3_count   0.33134    0.11400   2.906  0.00382 ** 
## category_code_LT01_4_count   0.83623    0.08641   9.678  < 2e-16 ***
## category_code_LT01_5_count   0.90184    0.06232  14.470  < 2e-16 ***
## category_code_LT01_6_count   0.45805    0.15195   3.014  0.00271 ** 
## category_code_LT01_12_count  0.07328    0.20606   0.356  0.72229    
## category_code_LT01_16_count  1.05303    1.17235   0.898  0.36951    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6282, Adjusted R-squared:  0.6237 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count 0.623740581096413 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9844 -0.7483  0.0018  0.8978  3.4708 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97690    0.08721 114.407  < 2e-16 ***
## category_code_LT01_3_count   0.34934    0.11276   3.098  0.00206 ** 
## category_code_LT01_4_count   0.81653    0.08910   9.164  < 2e-16 ***
## category_code_LT01_5_count   0.89822    0.06253  14.364  < 2e-16 ***
## category_code_LT01_6_count   0.46558    0.15091   3.085  0.00215 ** 
## category_code_LT01_13_count  0.13354    0.24264   0.550  0.58231    
## category_code_LT01_14_count  0.27493    0.32792   0.838  0.40220    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6283, Adjusted R-squared:  0.6237 
## F-statistic: 138.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count 0.623209186742556 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9859 -0.7544  0.0105  0.9187  3.4669 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97439    0.08722 114.355  < 2e-16 ***
## category_code_LT01_3_count   0.34796    0.11373   3.060  0.00234 ** 
## category_code_LT01_4_count   0.83474    0.08682   9.614  < 2e-16 ***
## category_code_LT01_5_count   0.90409    0.06218  14.539  < 2e-16 ***
## category_code_LT01_6_count   0.45567    0.15061   3.025  0.00261 ** 
## category_code_LT01_13_count  0.13173    0.24332   0.541  0.58848    
## category_code_LT01_15_count -0.07364    0.75589  -0.097  0.92244    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6278, Adjusted R-squared:  0.6232 
## F-statistic:   138 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_16_count 0.623849480124218 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9852 -0.7514  0.0024  0.9186  3.4716 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97465    0.08715 114.460  < 2e-16 ***
## category_code_LT01_3_count   0.33245    0.11374   2.923  0.00363 ** 
## category_code_LT01_4_count   0.83301    0.08657   9.622  < 2e-16 ***
## category_code_LT01_5_count   0.90262    0.06213  14.528  < 2e-16 ***
## category_code_LT01_6_count   0.46584    0.15082   3.089  0.00212 ** 
## category_code_LT01_13_count  0.14152    0.24277   0.583  0.56019    
## category_code_LT01_16_count  1.07837    1.17290   0.919  0.35834    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6284, Adjusted R-squared:  0.6238 
## F-statistic: 138.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count 0.623525666505831 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9850 -0.7417 -0.0020  0.9296  3.4700 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97706    0.08723 114.373  < 2e-16 ***
## category_code_LT01_3_count   0.35283    0.11369   3.104  0.00202 ** 
## category_code_LT01_4_count   0.82375    0.08844   9.314  < 2e-16 ***
## category_code_LT01_5_count   0.89884    0.06256  14.368  < 2e-16 ***
## category_code_LT01_6_count   0.46555    0.15107   3.082  0.00217 ** 
## category_code_LT01_14_count  0.27569    0.32808   0.840  0.40114    
## category_code_LT01_15_count -0.11299    0.75415  -0.150  0.88097    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6235 
## F-statistic: 138.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_16_count 0.624187690150887 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9843 -0.7477  0.0008  0.9287  3.4714 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97751    0.08715 114.483  < 2e-16 ***
## category_code_LT01_3_count   0.33647    0.11368   2.960  0.00323 ** 
## category_code_LT01_4_count   0.82130    0.08827   9.304  < 2e-16 ***
## category_code_LT01_5_count   0.89717    0.06251  14.353  < 2e-16 ***
## category_code_LT01_6_count   0.47615    0.15131   3.147  0.00175 ** 
## category_code_LT01_14_count  0.29017    0.32813   0.884  0.37696    
## category_code_LT01_16_count  1.10504    1.17304   0.942  0.34664    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6242 
## F-statistic: 138.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_15_count+category_code_LT01_16_count 0.623596178090807 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9860 -0.7479  0.0019  0.9329  3.4671 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97486    0.08718 114.420  < 2e-16 ***
## category_code_LT01_3_count   0.33563    0.11472   2.926  0.00360 ** 
## category_code_LT01_4_count   0.84043    0.08592   9.781  < 2e-16 ***
## category_code_LT01_5_count   0.90345    0.06215  14.536  < 2e-16 ***
## category_code_LT01_6_count   0.46511    0.15096   3.081  0.00218 ** 
## category_code_LT01_15_count -0.07232    0.75456  -0.096  0.92368    
## category_code_LT01_16_count  1.04844    1.17349   0.893  0.37206    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.382 on 491 degrees of freedom
## Multiple R-squared:  0.6281, Adjusted R-squared:  0.6236 
## F-statistic: 138.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 0.626373383017677 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0078 -0.7609  0.0578  0.8577  3.4411 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.98951    0.08673 115.180  < 2e-16 ***
## category_code_LT01_3_count  0.34143    0.11304   3.020  0.00266 ** 
## category_code_LT01_4_count  0.81824    0.08625   9.486  < 2e-16 ***
## category_code_LT01_5_count  0.91381    0.06241  14.642  < 2e-16 ***
## category_code_LT01_7_count  0.47646    0.15362   3.102  0.00204 ** 
## category_code_LT01_8_count -0.18893    0.27276  -0.693  0.48884    
## category_code_LT01_9_count  0.36387    0.22641   1.607  0.10867    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6309, Adjusted R-squared:  0.6264 
## F-statistic: 139.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 0.624808083358904 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9987 -0.7554  0.0522  0.8640  3.3574 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97613    0.09015 110.658  < 2e-16 ***
## category_code_LT01_3_count   0.35443    0.11383   3.114  0.00196 ** 
## category_code_LT01_4_count   0.82700    0.08622   9.592  < 2e-16 ***
## category_code_LT01_5_count   0.92000    0.06243  14.737  < 2e-16 ***
## category_code_LT01_7_count   0.49293    0.15361   3.209  0.00142 ** 
## category_code_LT01_8_count  -0.18012    0.27326  -0.659  0.51011    
## category_code_LT01_10_count  0.08223    0.11363   0.724  0.46963    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 0.630165200636706 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0168 -0.7735  0.0527  0.8651  3.4315 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99745    0.08626 115.894  < 2e-16 ***
## category_code_LT01_3_count   0.28703    0.11505   2.495  0.01293 *  
## category_code_LT01_4_count   0.71612    0.09477   7.556 2.04e-13 ***
## category_code_LT01_5_count   0.91535    0.06200  14.764  < 2e-16 ***
## category_code_LT01_7_count   0.39116    0.15720   2.488  0.01317 *  
## category_code_LT01_8_count  -0.15014    0.27144  -0.553  0.58043    
## category_code_LT01_11_count  0.32133    0.11623   2.765  0.00591 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6346, Adjusted R-squared:  0.6302 
## F-statistic: 142.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 0.624781187203298 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0126 -0.7658  0.0444  0.8656  3.4354 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99272    0.08689 115.009  < 2e-16 ***
## category_code_LT01_3_count   0.36285    0.11233   3.230  0.00132 ** 
## category_code_LT01_4_count   0.81929    0.08724   9.391  < 2e-16 ***
## category_code_LT01_5_count   0.91608    0.06266  14.619  < 2e-16 ***
## category_code_LT01_7_count   0.50029    0.15315   3.267  0.00116 ** 
## category_code_LT01_8_count  -0.18339    0.27340  -0.671  0.50267    
## category_code_LT01_12_count  0.14284    0.20439   0.699  0.48496    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 0.624414108032388 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0159 -0.7625  0.0395  0.8556  3.4306 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99351    0.08692 114.971  < 2e-16 ***
## category_code_LT01_3_count   0.36927    0.11200   3.297  0.00105 ** 
## category_code_LT01_4_count   0.82802    0.08660   9.562  < 2e-16 ***
## category_code_LT01_5_count   0.91971    0.06248  14.719  < 2e-16 ***
## category_code_LT01_7_count   0.49994    0.15434   3.239  0.00128 ** 
## category_code_LT01_8_count  -0.17521    0.27390  -0.640  0.52268    
## category_code_LT01_13_count  0.02198    0.24460   0.090  0.92845    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6289, Adjusted R-squared:  0.6244 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 0.624505954250154 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0157 -0.7571  0.0382  0.8594  3.4316 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99479    0.08698 114.913  < 2e-16 ***
## category_code_LT01_3_count   0.37118    0.11208   3.312 0.000996 ***
## category_code_LT01_4_count   0.82288    0.08776   9.377  < 2e-16 ***
## category_code_LT01_5_count   0.91762    0.06276  14.620  < 2e-16 ***
## category_code_LT01_7_count   0.49763    0.15360   3.240 0.001277 ** 
## category_code_LT01_8_count  -0.17804    0.27336  -0.651 0.515143    
## category_code_LT01_14_count  0.11720    0.32735   0.358 0.720488    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 0.624415559029627 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0162 -0.7634  0.0391  0.8547  3.4302 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99363    0.08692 114.972  < 2e-16 ***
## category_code_LT01_3_count   0.36792    0.11299   3.256  0.00121 ** 
## category_code_LT01_4_count   0.82803    0.08652   9.570  < 2e-16 ***
## category_code_LT01_5_count   0.92001    0.06248  14.726  < 2e-16 ***
## category_code_LT01_7_count   0.50211    0.15330   3.275  0.00113 ** 
## category_code_LT01_8_count  -0.17700    0.27338  -0.647  0.51764    
## category_code_LT01_15_count  0.07518    0.75294   0.100  0.92051    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6289, Adjusted R-squared:  0.6244 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 0.624790070185411 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0162 -0.7718  0.0324  0.8566  3.4305 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99412    0.08688 115.034  < 2e-16 ***
## category_code_LT01_3_count   0.35947    0.11281   3.186  0.00153 ** 
## category_code_LT01_4_count   0.82966    0.08620   9.625  < 2e-16 ***
## category_code_LT01_5_count   0.91931    0.06243  14.725  < 2e-16 ***
## category_code_LT01_7_count   0.50215    0.15314   3.279  0.00112 ** 
## category_code_LT01_8_count  -0.18601    0.27354  -0.680  0.49682    
## category_code_LT01_16_count  0.82631    1.16851   0.707  0.47981    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 0.626249700856632 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9884 -0.7603  0.0588  0.8760  3.4068 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97427    0.08995 110.883  < 2e-16 ***
## category_code_LT01_3_count   0.32946    0.11465   2.874  0.00423 ** 
## category_code_LT01_4_count   0.81741    0.08629   9.473  < 2e-16 ***
## category_code_LT01_5_count   0.90778    0.06176  14.698  < 2e-16 ***
## category_code_LT01_7_count   0.46752    0.15395   3.037  0.00252 ** 
## category_code_LT01_9_count   0.34714    0.22742   1.526  0.12754    
## category_code_LT01_10_count  0.06416    0.11393   0.563  0.57358    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6308, Adjusted R-squared:  0.6262 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 0.631603576987511 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0039 -0.7612  0.0472  0.8846  3.4488 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99212    0.08610 116.054  < 2e-16 ***
## category_code_LT01_3_count   0.26106    0.11592   2.252  0.02476 *  
## category_code_LT01_4_count   0.70807    0.09470   7.477 3.53e-13 ***
## category_code_LT01_5_count   0.90440    0.06133  14.747  < 2e-16 ***
## category_code_LT01_7_count   0.36671    0.15741   2.330  0.02023 *  
## category_code_LT01_9_count   0.33542    0.22490   1.491  0.13650    
## category_code_LT01_11_count  0.31682    0.11602   2.731  0.00654 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.367 on 491 degrees of freedom
## Multiple R-squared:  0.6361, Adjusted R-squared:  0.6316 
## F-statistic:   143 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 0.626341979538733 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9982 -0.7178  0.0437  0.8642  3.4564 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98691    0.08671 115.182  < 2e-16 ***
## category_code_LT01_3_count   0.33408    0.11342   2.946  0.00338 ** 
## category_code_LT01_4_count   0.80953    0.08729   9.274  < 2e-16 ***
## category_code_LT01_5_count   0.90378    0.06201  14.574  < 2e-16 ***
## category_code_LT01_7_count   0.47221    0.15357   3.075  0.00222 ** 
## category_code_LT01_9_count   0.35807    0.22634   1.582  0.11429    
## category_code_LT01_12_count  0.13499    0.20385   0.662  0.50816    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6309, Adjusted R-squared:  0.6263 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 0.626055265796367 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0013 -0.7325  0.0514  0.8492  3.4503 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98761    0.08673 115.155  < 2e-16 ***
## category_code_LT01_3_count   0.33952    0.11311   3.002  0.00282 ** 
## category_code_LT01_4_count   0.81632    0.08670   9.415  < 2e-16 ***
## category_code_LT01_5_count   0.90718    0.06179  14.681  < 2e-16 ***
## category_code_LT01_7_count   0.46864    0.15485   3.026  0.00260 ** 
## category_code_LT01_9_count   0.36368    0.22704   1.602  0.10984    
## category_code_LT01_13_count  0.06067    0.24426   0.248  0.80395    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6306, Adjusted R-squared:  0.6261 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 0.626052331607035 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0015 -0.7327  0.0420  0.8597  3.4505 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98862    0.08680 115.072  < 2e-16 ***
## category_code_LT01_3_count   0.34170    0.11324   3.017  0.00268 ** 
## category_code_LT01_4_count   0.81459    0.08774   9.284  < 2e-16 ***
## category_code_LT01_5_count   0.90607    0.06208  14.596  < 2e-16 ***
## category_code_LT01_7_count   0.47105    0.15395   3.060  0.00234 ** 
## category_code_LT01_9_count   0.35572    0.22696   1.567  0.11769    
## category_code_LT01_14_count  0.07875    0.32744   0.240  0.81005    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6306, Adjusted R-squared:  0.6261 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 0.626024814268335 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0019 -0.7358  0.0478  0.8606  3.4495 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98784    0.08673 115.154  < 2e-16 ***
## category_code_LT01_3_count   0.33793    0.11416   2.960  0.00322 ** 
## category_code_LT01_4_count   0.81734    0.08660   9.438  < 2e-16 ***
## category_code_LT01_5_count   0.90773    0.06179  14.690  < 2e-16 ***
## category_code_LT01_7_count   0.47413    0.15369   3.085  0.00215 ** 
## category_code_LT01_9_count   0.36063    0.22655   1.592  0.11207    
## category_code_LT01_15_count  0.11075    0.75171   0.147  0.88293    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 0.626312606097749 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0017 -0.7327  0.0422  0.8624  3.4595 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98822    0.08670 115.201  < 2e-16 ***
## category_code_LT01_3_count   0.33160    0.11386   2.912  0.00375 ** 
## category_code_LT01_4_count   0.81936    0.08627   9.497  < 2e-16 ***
## category_code_LT01_5_count   0.90685    0.06176  14.683  < 2e-16 ***
## category_code_LT01_7_count   0.47409    0.15357   3.087  0.00214 ** 
## category_code_LT01_9_count   0.35548    0.22643   1.570  0.11707    
## category_code_LT01_16_count  0.73684    1.16525   0.632  0.52745    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6308, Adjusted R-squared:  0.6263 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 0.630314440981374 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9949 -0.7686  0.0344  0.8899  3.3675 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97903    0.08948 111.528  < 2e-16 ***
## category_code_LT01_3_count   0.27065    0.11680   2.317  0.02090 *  
## category_code_LT01_4_count   0.71375    0.09477   7.532 2.43e-13 ***
## category_code_LT01_5_count   0.91030    0.06131  14.848  < 2e-16 ***
## category_code_LT01_7_count   0.37934    0.15750   2.409  0.01638 *  
## category_code_LT01_10_count  0.08009    0.11278   0.710  0.47796    
## category_code_LT01_11_count  0.32338    0.11613   2.785  0.00557 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.369 on 491 degrees of freedom
## Multiple R-squared:  0.6348, Adjusted R-squared:  0.6303 
## F-statistic: 142.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 0.624799871607533 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9902 -0.7571  0.0441  0.8854  3.3741 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97439    0.09013 110.669  < 2e-16 ***
## category_code_LT01_3_count   0.34750    0.11415   3.044  0.00246 ** 
## category_code_LT01_4_count   0.81833    0.08726   9.378  < 2e-16 ***
## category_code_LT01_5_count   0.91021    0.06201  14.678  < 2e-16 ***
## category_code_LT01_7_count   0.48888    0.15355   3.184  0.00155 ** 
## category_code_LT01_10_count  0.07831    0.11369   0.689  0.49128    
## category_code_LT01_12_count  0.13305    0.20439   0.651  0.51540    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 0.624486431443256 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9930 -0.7530  0.0503  0.8720  3.3673 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97469    0.09016 110.628  < 2e-16 ***
## category_code_LT01_3_count   0.35306    0.11387   3.101  0.00204 ** 
## category_code_LT01_4_count   0.82615    0.08662   9.538  < 2e-16 ***
## category_code_LT01_5_count   0.91381    0.06178  14.790  < 2e-16 ***
## category_code_LT01_7_count   0.48784    0.15466   3.154  0.00171 ** 
## category_code_LT01_10_count  0.08069    0.11368   0.710  0.47816    
## category_code_LT01_13_count  0.02839    0.24415   0.116  0.90748    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 0.62450557296998 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9939 -0.7527  0.0305  0.8734  3.3721 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97644    0.09061 110.107   <2e-16 ***
## category_code_LT01_3_count   0.35510    0.11428   3.107   0.0020 ** 
## category_code_LT01_4_count   0.82388    0.08776   9.387   <2e-16 ***
## category_code_LT01_5_count   0.91266    0.06212  14.692   <2e-16 ***
## category_code_LT01_7_count   0.48823    0.15385   3.173   0.0016 ** 
## category_code_LT01_10_count  0.07587    0.11656   0.651   0.5154    
## category_code_LT01_14_count  0.06591    0.33568   0.196   0.8444    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 0.624477875052234 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9932 -0.7536  0.0491  0.8671  3.3671 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97479    0.09019 110.596  < 2e-16 ***
## category_code_LT01_3_count   0.35253    0.11469   3.074  0.00223 ** 
## category_code_LT01_4_count   0.82673    0.08654   9.554  < 2e-16 ***
## category_code_LT01_5_count   0.91401    0.06179  14.792  < 2e-16 ***
## category_code_LT01_7_count   0.49022    0.15371   3.189  0.00152 ** 
## category_code_LT01_10_count  0.08060    0.11390   0.708  0.47951    
## category_code_LT01_15_count  0.03645    0.75437   0.048  0.96149    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 0.624804352000112 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9934 -0.7515  0.0377  0.8667  3.3692 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97556    0.09014 110.672  < 2e-16 ***
## category_code_LT01_3_count   0.34429    0.11462   3.004  0.00280 ** 
## category_code_LT01_4_count   0.82797    0.08623   9.602  < 2e-16 ***
## category_code_LT01_5_count   0.91315    0.06176  14.786  < 2e-16 ***
## category_code_LT01_7_count   0.49051    0.15354   3.195  0.00149 ** 
## category_code_LT01_10_count  0.07884    0.11366   0.694  0.48825    
## category_code_LT01_16_count  0.76528    1.16761   0.655  0.51250    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 0.629937746435471 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0122 -0.7820  0.0605  0.8761  3.4380 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99616    0.08627 115.870  < 2e-16 ***
## category_code_LT01_3_count   0.28531    0.11505   2.480  0.01348 *  
## category_code_LT01_4_count   0.71553    0.09483   7.546  2.2e-13 ***
## category_code_LT01_5_count   0.91063    0.06159  14.786  < 2e-16 ***
## category_code_LT01_7_count   0.38721    0.15738   2.460  0.01422 *  
## category_code_LT01_11_count  0.32563    0.12054   2.701  0.00714 ** 
## category_code_LT01_12_count -0.01326    0.21045  -0.063  0.94979    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6344, Adjusted R-squared:  0.6299 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 0.629936992888347 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0118 -0.7818  0.0600  0.8769  3.4385 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99602    0.08625 115.891  < 2e-16 ***
## category_code_LT01_3_count   0.28518    0.11504   2.479   0.0135 *  
## category_code_LT01_4_count   0.71499    0.09503   7.524 2.56e-13 ***
## category_code_LT01_5_count   0.91022    0.06135  14.837  < 2e-16 ***
## category_code_LT01_7_count   0.38684    0.15805   2.448   0.0147 *  
## category_code_LT01_11_count  0.32343    0.11623   2.783   0.0056 ** 
## category_code_LT01_13_count  0.01321    0.24242   0.054   0.9566    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6344, Adjusted R-squared:  0.6299 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 0.629999179107424 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0116 -0.7839  0.0624  0.8768  3.4395 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99702    0.08631 115.827  < 2e-16 ***
## category_code_LT01_3_count   0.28682    0.11516   2.491  0.01308 *  
## category_code_LT01_4_count   0.71087    0.09601   7.404  5.8e-13 ***
## category_code_LT01_5_count   0.90843    0.06166  14.734  < 2e-16 ***
## category_code_LT01_7_count   0.38478    0.15745   2.444  0.01488 *  
## category_code_LT01_11_count  0.32288    0.11621   2.779  0.00567 ** 
## category_code_LT01_14_count  0.09503    0.32500   0.292  0.77011    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6345, Adjusted R-squared:   0.63 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 0.629935229401434 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0118 -0.7818  0.0582  0.8768  3.4385 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99603    0.08625 115.890  < 2e-16 ***
## category_code_LT01_3_count   0.28556    0.11585   2.465  0.01405 *  
## category_code_LT01_4_count   0.71549    0.09494   7.537 2.34e-13 ***
## category_code_LT01_5_count   0.91024    0.06135  14.836  < 2e-16 ***
## category_code_LT01_7_count   0.38761    0.15727   2.465  0.01406 *  
## category_code_LT01_11_count  0.32373    0.11630   2.784  0.00558 ** 
## category_code_LT01_15_count -0.01877    0.74803  -0.025  0.97999    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6344, Adjusted R-squared:  0.6299 
## F-statistic:   142 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 0.630256420933286 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0118 -0.7810  0.0654  0.8806  3.4389 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99646    0.08622 115.944  < 2e-16 ***
## category_code_LT01_3_count   0.27621    0.11581   2.385  0.01746 *  
## category_code_LT01_4_count   0.71647    0.09476   7.561 1.99e-13 ***
## category_code_LT01_5_count   0.90950    0.06132  14.831  < 2e-16 ***
## category_code_LT01_7_count   0.38836    0.15706   2.473  0.01375 *  
## category_code_LT01_11_count  0.32288    0.11614   2.780  0.00564 ** 
## category_code_LT01_16_count  0.75728    1.15868   0.654  0.51369    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.37 on 491 degrees of freedom
## Multiple R-squared:  0.6347, Adjusted R-squared:  0.6303 
## F-statistic: 142.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 0.624446932507703 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0066 -0.7575  0.0511  0.8627  3.4439 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99095    0.08689 114.987  < 2e-16 ***
## category_code_LT01_3_count   0.36143    0.11237   3.216  0.00138 ** 
## category_code_LT01_4_count   0.81880    0.08761   9.346  < 2e-16 ***
## category_code_LT01_5_count   0.90994    0.06205  14.665  < 2e-16 ***
## category_code_LT01_7_count   0.49510    0.15423   3.210  0.00141 ** 
## category_code_LT01_12_count  0.13746    0.20443   0.672  0.50164    
## category_code_LT01_13_count  0.02735    0.24420   0.112  0.91086    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6244 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 0.624504782695491 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0065 -0.7502  0.0201  0.8760  3.4447 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99203    0.08695 114.916  < 2e-16 ***
## category_code_LT01_3_count   0.36325    0.11249   3.229  0.00133 ** 
## category_code_LT01_4_count   0.81510    0.08861   9.199  < 2e-16 ***
## category_code_LT01_5_count   0.90829    0.06232  14.574  < 2e-16 ***
## category_code_LT01_7_count   0.49387    0.15354   3.217  0.00138 ** 
## category_code_LT01_12_count  0.13327    0.20498   0.650  0.51590    
## category_code_LT01_14_count  0.09751    0.32835   0.297  0.76661    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 0.624446545702858 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0068 -0.7563  0.0508  0.8715  3.4435 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99106    0.08689 114.987  < 2e-16 ***
## category_code_LT01_3_count   0.35989    0.11339   3.174  0.00160 ** 
## category_code_LT01_4_count   0.81884    0.08759   9.348  < 2e-16 ***
## category_code_LT01_5_count   0.91019    0.06205  14.668  < 2e-16 ***
## category_code_LT01_7_count   0.49769    0.15323   3.248  0.00124 ** 
## category_code_LT01_12_count  0.13860    0.20442   0.678  0.49806    
## category_code_LT01_15_count  0.08264    0.75308   0.110  0.91267    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6244 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 0.624792304203452 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0065 -0.7462  0.0269  0.8727  3.4443 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99143    0.08685 115.043  < 2e-16 ***
## category_code_LT01_3_count   0.35186    0.11321   3.108  0.00199 ** 
## category_code_LT01_4_count   0.82046    0.08725   9.404  < 2e-16 ***
## category_code_LT01_5_count   0.90919    0.06203  14.658  < 2e-16 ***
## category_code_LT01_7_count   0.49749    0.15308   3.250  0.00123 ** 
## category_code_LT01_12_count  0.13934    0.20427   0.682  0.49547    
## category_code_LT01_16_count  0.79552    1.16721   0.682  0.49584    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 0.624195080727112 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0097 -0.7611  0.0481  0.8593  3.4401 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99301    0.08697 114.898  < 2e-16 ***
## category_code_LT01_3_count   0.36949    0.11211   3.296  0.00105 ** 
## category_code_LT01_4_count   0.82199    0.08816   9.324  < 2e-16 ***
## category_code_LT01_5_count   0.91153    0.06214  14.669  < 2e-16 ***
## category_code_LT01_7_count   0.49219    0.15469   3.182  0.00156 ** 
## category_code_LT01_13_count  0.03249    0.24421   0.133  0.89420    
## category_code_LT01_14_count  0.11475    0.32747   0.350  0.72619    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6242 
## F-statistic: 138.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 0.624109034152621 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0102 -0.7634  0.0518  0.8566  3.4386 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99188    0.08692 114.956  < 2e-16 ***
## category_code_LT01_3_count   0.36623    0.11304   3.240  0.00128 ** 
## category_code_LT01_4_count   0.82697    0.08696   9.510  < 2e-16 ***
## category_code_LT01_5_count   0.91391    0.06183  14.781  < 2e-16 ***
## category_code_LT01_7_count   0.49656    0.15434   3.217  0.00138 ** 
## category_code_LT01_13_count  0.03325    0.24469   0.136  0.89196    
## category_code_LT01_15_count  0.07679    0.75465   0.102  0.91899    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6241 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 0.624454903788067 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0099 -0.7626  0.0480  0.8564  3.4393 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99226    0.08688 115.013  < 2e-16 ***
## category_code_LT01_3_count   0.35809    0.11287   3.173  0.00161 ** 
## category_code_LT01_4_count   0.82845    0.08660   9.567  < 2e-16 ***
## category_code_LT01_5_count   0.91292    0.06180  14.772  < 2e-16 ***
## category_code_LT01_7_count   0.49608    0.15422   3.217  0.00138 ** 
## category_code_LT01_13_count  0.03767    0.24427   0.154  0.87751    
## category_code_LT01_16_count  0.79468    1.16844   0.680  0.49675    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 0.624187298208454 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0100 -0.7628  0.0479  0.8669  3.4397 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99311    0.08697 114.897  < 2e-16 ***
## category_code_LT01_3_count   0.36837    0.11312   3.256  0.00121 ** 
## category_code_LT01_4_count   0.82248    0.08805   9.341  < 2e-16 ***
## category_code_LT01_5_count   0.91183    0.06215  14.672  < 2e-16 ***
## category_code_LT01_7_count   0.49509    0.15369   3.221  0.00136 ** 
## category_code_LT01_14_count  0.11380    0.32753   0.347  0.72840    
## category_code_LT01_15_count  0.06540    0.75327   0.087  0.93085    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6242 
## F-statistic: 138.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 0.624546512264453 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0097 -0.7571  0.0445  0.8682  3.4405 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99362    0.08694 114.955  < 2e-16 ***
## category_code_LT01_3_count   0.36003    0.11292   3.188  0.00152 ** 
## category_code_LT01_4_count   0.82349    0.08775   9.384  < 2e-16 ***
## category_code_LT01_5_count   0.91066    0.06211  14.661  < 2e-16 ***
## category_code_LT01_7_count   0.49467    0.15352   3.222  0.00136 ** 
## category_code_LT01_14_count  0.12414    0.32761   0.379  0.70490    
## category_code_LT01_16_count  0.80738    1.16864   0.691  0.48997    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 0.624448399414603 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0103 -0.7632  0.0435  0.8653  3.4388 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99240    0.08688 115.012  < 2e-16 ***
## category_code_LT01_3_count   0.35647    0.11394   3.129  0.00186 ** 
## category_code_LT01_4_count   0.82879    0.08652   9.579  < 2e-16 ***
## category_code_LT01_5_count   0.91327    0.06180  14.777  < 2e-16 ***
## category_code_LT01_7_count   0.49952    0.15322   3.260  0.00119 ** 
## category_code_LT01_15_count  0.09314    0.75361   0.124  0.90168    
## category_code_LT01_16_count  0.79462    1.16884   0.680  0.49693    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6244 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 0.619520593633708 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9948 -0.7599  0.0630  0.8807  3.3649 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97034    0.09077 109.844  < 2e-16 ***
## category_code_LT01_3_count   0.33976    0.11565   2.938  0.00346 ** 
## category_code_LT01_4_count   0.90790    0.08175  11.106  < 2e-16 ***
## category_code_LT01_5_count   0.92271    0.06292  14.665  < 2e-16 ***
## category_code_LT01_8_count  -0.16875    0.27518  -0.613  0.54001    
## category_code_LT01_9_count   0.41709    0.22851   1.825  0.06856 .  
## category_code_LT01_10_count  0.08908    0.11469   0.777  0.43773    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6241, Adjusted R-squared:  0.6195 
## F-statistic: 135.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 0.627729201792092 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0134 -0.7732  0.0549  0.8857  3.4350 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99412    0.08659 115.425  < 2e-16 ***
## category_code_LT01_3_count   0.25552    0.11652   2.193 0.028779 *  
## category_code_LT01_4_count   0.75261    0.09334   8.063 5.74e-15 ***
## category_code_LT01_5_count   0.91521    0.06227  14.697  < 2e-16 ***
## category_code_LT01_8_count  -0.13903    0.27227  -0.511 0.609833    
## category_code_LT01_9_count   0.38617    0.22529   1.714 0.087140 .  
## category_code_LT01_11_count  0.38231    0.11302   3.383 0.000775 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6322, Adjusted R-squared:  0.6277 
## F-statistic: 140.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 0.619449863892564 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0097 -0.7777  0.0554  0.8866  3.4373 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98817    0.08754 114.101  < 2e-16 ***
## category_code_LT01_3_count   0.34822    0.11439   3.044  0.00246 ** 
## category_code_LT01_4_count   0.90094    0.08284  10.876  < 2e-16 ***
## category_code_LT01_5_count   0.91853    0.06316  14.544  < 2e-16 ***
## category_code_LT01_8_count  -0.17212    0.27533  -0.625  0.53217    
## category_code_LT01_9_count   0.43382    0.22732   1.908  0.05692 .  
## category_code_LT01_12_count  0.14726    0.20583   0.715  0.47469    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.624,  Adjusted R-squared:  0.6194 
## F-statistic: 135.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 0.619327998779237 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0119 -0.7781  0.0543  0.8804  3.4341 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98858    0.08755 114.094  < 2e-16 ***
## category_code_LT01_3_count   0.35283    0.11407   3.093  0.00209 ** 
## category_code_LT01_4_count   0.90358    0.08259  10.940  < 2e-16 ***
## category_code_LT01_5_count   0.92101    0.06298  14.625  < 2e-16 ***
## category_code_LT01_8_count  -0.15600    0.27565  -0.566  0.57170    
## category_code_LT01_9_count   0.44345    0.22774   1.947  0.05208 .  
## category_code_LT01_13_count  0.14580    0.24488   0.595  0.55186    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6239, Adjusted R-squared:  0.6193 
## F-statistic: 135.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 0.619207238464798 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0130 -0.7711  0.0535  0.8737  3.4336 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99065    0.08763 114.006  < 2e-16 ***
## category_code_LT01_3_count   0.35754    0.11419   3.131  0.00185 ** 
## category_code_LT01_4_count   0.90288    0.08364  10.795  < 2e-16 ***
## category_code_LT01_5_count   0.91965    0.06325  14.540  < 2e-16 ***
## category_code_LT01_8_count  -0.16687    0.27528  -0.606  0.54466    
## category_code_LT01_9_count   0.42771    0.22804   1.876  0.06130 .  
## category_code_LT01_14_count  0.14697    0.32974   0.446  0.65600    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6238, Adjusted R-squared:  0.6192 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 0.619056283294917 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0134 -0.7782  0.0505  0.8840  3.4320 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98906    0.08758 114.061  < 2e-16 ***
## category_code_LT01_3_count   0.35393    0.11512   3.074  0.00223 ** 
## category_code_LT01_4_count   0.91047    0.08196  11.109  < 2e-16 ***
## category_code_LT01_5_count   0.92252    0.06297  14.650  < 2e-16 ***
## category_code_LT01_8_count  -0.16542    0.27532  -0.601  0.54824    
## category_code_LT01_9_count   0.43596    0.22758   1.916  0.05600 .  
## category_code_LT01_15_count  0.04805    0.75840   0.063  0.94951    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 0.619366929707015 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0135 -0.7766  0.0462  0.8833  3.4320 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98957    0.08754 114.110   <2e-16 ***
## category_code_LT01_3_count   0.34622    0.11483   3.015   0.0027 ** 
## category_code_LT01_4_count   0.91198    0.08169  11.164   <2e-16 ***
## category_code_LT01_5_count   0.92201    0.06293  14.651   <2e-16 ***
## category_code_LT01_8_count  -0.17348    0.27550  -0.630   0.5292    
## category_code_LT01_9_count   0.43164    0.22741   1.898   0.0583 .  
## category_code_LT01_16_count  0.74899    1.17731   0.636   0.5249    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.624,  Adjusted R-squared:  0.6194 
## F-statistic: 135.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 0.626116277498075 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0009 -0.7624  0.0528  0.8734  3.3331 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97700    0.09000 110.858  < 2e-16 ***
## category_code_LT01_3_count   0.26459    0.11745   2.253 0.024719 *  
## category_code_LT01_4_count   0.76054    0.09339   8.144 3.19e-15 ***
## category_code_LT01_5_count   0.92192    0.06228  14.802  < 2e-16 ***
## category_code_LT01_8_count  -0.12874    0.27277  -0.472 0.637164    
## category_code_LT01_10_count  0.10164    0.11312   0.899 0.369350    
## category_code_LT01_11_count  0.39248    0.11305   3.472 0.000563 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6306, Adjusted R-squared:  0.6261 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 0.61731832266408 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9972 -0.7597  0.0529  0.8807  3.3282 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97017    0.09103 109.525  < 2e-16 ***
## category_code_LT01_3_count   0.36282    0.11521   3.149  0.00174 ** 
## category_code_LT01_4_count   0.91512    0.08263  11.075  < 2e-16 ***
## category_code_LT01_5_count   0.92639    0.06320  14.657  < 2e-16 ***
## category_code_LT01_8_count  -0.16084    0.27602  -0.583  0.56036    
## category_code_LT01_10_count  0.10782    0.11448   0.942  0.34675    
## category_code_LT01_12_count  0.14411    0.20653   0.698  0.48564    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 0.617097549462716 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9995 -0.7600  0.0505  0.8644  3.3232 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97047    0.09106 109.498  < 2e-16 ***
## category_code_LT01_3_count   0.36815    0.11492   3.204  0.00145 ** 
## category_code_LT01_4_count   0.91958    0.08230  11.174  < 2e-16 ***
## category_code_LT01_5_count   0.92927    0.06302  14.746  < 2e-16 ***
## category_code_LT01_8_count  -0.14687    0.27641  -0.531  0.59542    
## category_code_LT01_10_count  0.10917    0.11449   0.954  0.34079    
## category_code_LT01_13_count  0.11065    0.24528   0.451  0.65209    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 0.617051074202533 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0018 -0.7635  0.0517  0.8577  3.3309 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97389    0.09152 108.979  < 2e-16 ***
## category_code_LT01_3_count   0.37260    0.11531   3.231  0.00131 ** 
## category_code_LT01_4_count   0.91794    0.08346  10.998  < 2e-16 ***
## category_code_LT01_5_count   0.92769    0.06334  14.646  < 2e-16 ***
## category_code_LT01_8_count  -0.15539    0.27597  -0.563  0.57365    
## category_code_LT01_10_count  0.10063    0.11749   0.857  0.39213    
## category_code_LT01_14_count  0.12840    0.33847   0.379  0.70459    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 0.616942298759624 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9999 -0.7598  0.0420  0.8649  3.3203 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97028    0.09110 109.443  < 2e-16 ***
## category_code_LT01_3_count   0.36988    0.11574   3.196  0.00148 ** 
## category_code_LT01_4_count   0.92519    0.08170  11.324  < 2e-16 ***
## category_code_LT01_5_count   0.93012    0.06302  14.760  < 2e-16 ***
## category_code_LT01_8_count  -0.15405    0.27600  -0.558  0.57700    
## category_code_LT01_10_count  0.11116    0.11468   0.969  0.33286    
## category_code_LT01_15_count -0.05072    0.76139  -0.067  0.94692    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.6169 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 0.61727655736165 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0007 -0.7625  0.0458  0.8756  3.3224 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97137    0.09105 109.519  < 2e-16 ***
## category_code_LT01_3_count   0.36001    0.11568   3.112  0.00197 ** 
## category_code_LT01_4_count   0.92586    0.08148  11.364  < 2e-16 ***
## category_code_LT01_5_count   0.92973    0.06297  14.764  < 2e-16 ***
## category_code_LT01_8_count  -0.16278    0.27618  -0.589  0.55586    
## category_code_LT01_10_count  0.10866    0.11446   0.949  0.34292    
## category_code_LT01_16_count  0.77708    1.18057   0.658  0.51070    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 0.625526500979463 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0234 -0.7704  0.0462  0.8723  3.4218 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99887    0.08682 115.172  < 2e-16 ***
## category_code_LT01_3_count   0.28319    0.11577   2.446 0.014790 *  
## category_code_LT01_4_count   0.76413    0.09340   8.181 2.43e-15 ***
## category_code_LT01_5_count   0.92283    0.06253  14.758  < 2e-16 ***
## category_code_LT01_8_count  -0.12165    0.27319  -0.445 0.656289    
## category_code_LT01_11_count  0.40038    0.11721   3.416 0.000688 ***
## category_code_LT01_12_count -0.03829    0.21157  -0.181 0.856441    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6255 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 0.625567218400191 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0219 -0.7677  0.0487  0.8727  3.4240 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99838    0.08680 115.190  < 2e-16 ***
## category_code_LT01_3_count   0.28270    0.11576   2.442 0.014950 *  
## category_code_LT01_4_count   0.76122    0.09381   8.114 3.96e-15 ***
## category_code_LT01_5_count   0.92134    0.06236  14.775  < 2e-16 ***
## category_code_LT01_8_count  -0.11926    0.27335  -0.436 0.662817    
## category_code_LT01_11_count  0.39300    0.11328   3.469 0.000568 ***
## category_code_LT01_13_count  0.07127    0.24281   0.294 0.769243    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6256 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 0.625660914632894 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0220 -0.7645  0.0512  0.8635  3.4248 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00011    0.08685 115.142  < 2e-16 ***
## category_code_LT01_3_count   0.28551    0.11588   2.464 0.014087 *  
## category_code_LT01_4_count   0.75625    0.09484   7.974 1.09e-14 ***
## category_code_LT01_5_count   0.91901    0.06264  14.670  < 2e-16 ***
## category_code_LT01_8_count  -0.12589    0.27291  -0.461 0.644813    
## category_code_LT01_11_count  0.39278    0.11318   3.470 0.000566 ***
## category_code_LT01_14_count  0.14918    0.32625   0.457 0.647694    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6257 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 0.62551334990949 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0223 -0.7701  0.0444  0.8737  3.4234 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99851    0.08681 115.183  < 2e-16 ***
## category_code_LT01_3_count   0.28463    0.11658   2.442 0.014978 *  
## category_code_LT01_4_count   0.76441    0.09350   8.176 2.52e-15 ***
## category_code_LT01_5_count   0.92171    0.06235  14.782  < 2e-16 ***
## category_code_LT01_8_count  -0.12349    0.27294  -0.452 0.651158    
## category_code_LT01_11_count  0.39530    0.11318   3.493 0.000521 ***
## category_code_LT01_15_count -0.09366    0.75185  -0.125 0.900914    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6255 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 0.625831575980941 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0227 -0.7665  0.0446  0.8761  3.4231 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99909    0.08677 115.237  < 2e-16 ***
## category_code_LT01_3_count   0.27388    0.11652   2.350 0.019148 *  
## category_code_LT01_4_count   0.76512    0.09337   8.195  2.2e-15 ***
## category_code_LT01_5_count   0.92144    0.06231  14.788  < 2e-16 ***
## category_code_LT01_8_count  -0.13245    0.27313  -0.485 0.627942    
## category_code_LT01_11_count  0.39410    0.11307   3.485 0.000535 ***
## category_code_LT01_16_count  0.76798    1.16693   0.658 0.510770    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6258 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 0.616790315718456 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0190 -0.7704  0.0485  0.8686  3.4252 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99274    0.08781 113.802  < 2e-16 ***
## category_code_LT01_3_count   0.38162    0.11337   3.366 0.000822 ***
## category_code_LT01_4_count   0.91404    0.08334  10.968  < 2e-16 ***
## category_code_LT01_5_count   0.92537    0.06328  14.624  < 2e-16 ***
## category_code_LT01_8_count  -0.14862    0.27665  -0.537 0.591363    
## category_code_LT01_12_count  0.14827    0.20663   0.718 0.473385    
## category_code_LT01_13_count  0.11225    0.24538   0.457 0.647534    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6168 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 0.616847535083698 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0195 -0.7680  0.0535  0.8601  3.4256 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99488    0.08787 113.744  < 2e-16 ***
## category_code_LT01_3_count   0.38542    0.11347   3.397 0.000737 ***
## category_code_LT01_4_count   0.90983    0.08443  10.776  < 2e-16 ***
## category_code_LT01_5_count   0.92301    0.06354  14.527  < 2e-16 ***
## category_code_LT01_8_count  -0.15799    0.27617  -0.572 0.567538    
## category_code_LT01_12_count  0.14239    0.20718   0.687 0.492213    
## category_code_LT01_14_count  0.17589    0.33085   0.532 0.595218    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6215, Adjusted R-squared:  0.6168 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 0.616627060830846 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0199 -0.7747  0.0420  0.8709  3.4239 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.993001   0.087827 113.780  < 2e-16 ***
## category_code_LT01_3_count   0.382453   0.114391   3.343 0.000891 ***
## category_code_LT01_4_count   0.919145   0.082840  11.095  < 2e-16 ***
## category_code_LT01_5_count   0.926280   0.063278  14.638  < 2e-16 ***
## category_code_LT01_8_count  -0.156133   0.276237  -0.565 0.572187    
## category_code_LT01_12_count  0.151164   0.206647   0.732 0.464820    
## category_code_LT01_15_count  0.007816   0.760522   0.010 0.991804    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 0.617000468207576 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0201 -0.7761  0.0344  0.8770  3.4240 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99353    0.08779 113.840  < 2e-16 ***
## category_code_LT01_3_count   0.37272    0.11422   3.263  0.00118 ** 
## category_code_LT01_4_count   0.92013    0.08256  11.145  < 2e-16 ***
## category_code_LT01_5_count   0.92569    0.06324  14.639  < 2e-16 ***
## category_code_LT01_8_count  -0.16532    0.27641  -0.598  0.55006    
## category_code_LT01_12_count  0.15267    0.20650   0.739  0.46006    
## category_code_LT01_16_count  0.81695    1.18063   0.692  0.48929    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616657955405408 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0220 -0.7756  0.0512  0.8539  3.4222 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99563    0.08788 113.739  < 2e-16 ***
## category_code_LT01_3_count   0.39110    0.11308   3.459  0.00059 ***
## category_code_LT01_4_count   0.91288    0.08432  10.826  < 2e-16 ***
## category_code_LT01_5_count   0.92543    0.06339  14.599  < 2e-16 ***
## category_code_LT01_8_count  -0.14382    0.27654  -0.520  0.60325    
## category_code_LT01_13_count  0.11748    0.24531   0.479  0.63223    
## category_code_LT01_14_count  0.19381    0.32989   0.587  0.55714    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6167 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616388911787313 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0226 -0.7832  0.0468  0.8575  3.4200 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99362    0.08785 113.761  < 2e-16 ***
## category_code_LT01_3_count   0.38809    0.11404   3.403 0.000721 ***
## category_code_LT01_4_count   0.92371    0.08254  11.191  < 2e-16 ***
## category_code_LT01_5_count   0.92931    0.06309  14.729  < 2e-16 ***
## category_code_LT01_8_count  -0.14132    0.27661  -0.511 0.609647    
## category_code_LT01_13_count  0.11792    0.24591   0.480 0.631774    
## category_code_LT01_15_count  0.01779    0.76213   0.023 0.981385    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 0.616771024009328 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0227 -0.7834  0.0375  0.8612  3.4201 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99415    0.08781 113.822  < 2e-16 ***
## category_code_LT01_3_count   0.37845    0.11387   3.323 0.000956 ***
## category_code_LT01_4_count   0.92463    0.08222  11.246  < 2e-16 ***
## category_code_LT01_5_count   0.92868    0.06305  14.729  < 2e-16 ***
## category_code_LT01_8_count  -0.15017    0.27676  -0.543 0.587654    
## category_code_LT01_13_count  0.12327    0.24541   0.502 0.615670    
## category_code_LT01_16_count  0.82720    1.18157   0.700 0.484208    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6168 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 0.61647914413091 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0229 -0.7794  0.0482  0.8549  3.4209 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99591    0.08790 113.715  < 2e-16 ***
## category_code_LT01_3_count   0.39253    0.11408   3.441 0.000629 ***
## category_code_LT01_4_count   0.91859    0.08373  10.971  < 2e-16 ***
## category_code_LT01_5_count   0.92642    0.06339  14.613  < 2e-16 ***
## category_code_LT01_8_count  -0.15147    0.27615  -0.549 0.583585    
## category_code_LT01_14_count  0.19399    0.33002   0.588 0.556928    
## category_code_LT01_15_count -0.01337    0.76055  -0.018 0.985980    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6165 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 0.616872808023608 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0231 -0.7777  0.0392  0.8548  3.4210 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99659    0.08786 113.778  < 2e-16 ***
## category_code_LT01_3_count   0.38232    0.11389   3.357 0.000849 ***
## category_code_LT01_4_count   0.91895    0.08348  11.008  < 2e-16 ***
## category_code_LT01_5_count   0.92570    0.06335  14.613  < 2e-16 ***
## category_code_LT01_8_count  -0.16104    0.27632  -0.583 0.560292    
## category_code_LT01_14_count  0.20426    0.33012   0.619 0.536379    
## category_code_LT01_16_count  0.83975    1.18191   0.711 0.477730    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6215, Adjusted R-squared:  0.6169 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 0.616574491037919 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0238 -0.7840  0.0348  0.8584  3.4186 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99445    0.08783 113.795  < 2e-16 ***
## category_code_LT01_3_count   0.37956    0.11493   3.302  0.00103 ** 
## category_code_LT01_4_count   0.93036    0.08163  11.397  < 2e-16 ***
## category_code_LT01_5_count   0.92981    0.06305  14.747  < 2e-16 ***
## category_code_LT01_8_count  -0.15809    0.27640  -0.572  0.56762    
## category_code_LT01_15_count  0.01735    0.76110   0.023  0.98182    
## category_code_LT01_16_count  0.80863    1.18239   0.684  0.49437    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.62792530434044 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9918 -0.7574  0.0499  0.9031  3.3686 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97565    0.08976 111.142  < 2e-16 ***
## category_code_LT01_3_count   0.24055    0.11798   2.039 0.041985 *  
## category_code_LT01_4_count   0.74942    0.09335   8.028 7.37e-15 ***
## category_code_LT01_5_count   0.91070    0.06157  14.790  < 2e-16 ***
## category_code_LT01_9_count   0.36568    0.22631   1.616 0.106762    
## category_code_LT01_10_count  0.08176    0.11342   0.721 0.471324    
## category_code_LT01_11_count  0.38264    0.11295   3.388 0.000762 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6324, Adjusted R-squared:  0.6279 
## F-statistic: 140.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 0.619574089308694 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9866 -0.7583  0.0565  0.8970  3.3829 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96873    0.09074 109.864  < 2e-16 ***
## category_code_LT01_3_count   0.33298    0.11596   2.871  0.00426 ** 
## category_code_LT01_4_count   0.89838    0.08289  10.838  < 2e-16 ***
## category_code_LT01_5_count   0.91320    0.06250  14.611  < 2e-16 ***
## category_code_LT01_9_count   0.41194    0.22840   1.804  0.07191 .  
## category_code_LT01_10_count  0.08519    0.11474   0.742  0.45816    
## category_code_LT01_12_count  0.13731    0.20580   0.667  0.50496    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6242, Adjusted R-squared:  0.6196 
## F-statistic: 135.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 0.61951006840303 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9889 -0.7587  0.0682  0.8852  3.3747 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96916    0.09074 109.860  < 2e-16 ***
## category_code_LT01_3_count   0.33717    0.11567   2.915  0.00372 ** 
## category_code_LT01_4_count   0.90029    0.08264  10.895  < 2e-16 ***
## category_code_LT01_5_count   0.91593    0.06227  14.710  < 2e-16 ***
## category_code_LT01_9_count   0.42188    0.22889   1.843  0.06590 .  
## category_code_LT01_10_count  0.08552    0.11475   0.745  0.45648    
## category_code_LT01_13_count  0.14725    0.24459   0.602  0.54742    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6241, Adjusted R-squared:  0.6195 
## F-statistic: 135.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 0.619288196721725 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9908 -0.7595  0.0641  0.8831  3.3694 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97154    0.09123 109.304  < 2e-16 ***
## category_code_LT01_3_count   0.34168    0.11614   2.942  0.00342 ** 
## category_code_LT01_4_count   0.90273    0.08363  10.794  < 2e-16 ***
## category_code_LT01_5_count   0.91524    0.06260  14.620  < 2e-16 ***
## category_code_LT01_9_count   0.40959    0.22882   1.790  0.07407 .  
## category_code_LT01_10_count  0.08079    0.11759   0.687  0.49241    
## category_code_LT01_14_count  0.09323    0.33796   0.276  0.78277    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6239, Adjusted R-squared:  0.6193 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 0.619229235698052 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9896 -0.7586  0.0648  0.8870  3.3695 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.969033   0.090801 109.789  < 2e-16 ***
## category_code_LT01_3_count  0.338695   0.116573   2.905  0.00383 ** 
## category_code_LT01_4_count  0.907523   0.082014  11.066  < 2e-16 ***
## category_code_LT01_5_count  0.917061   0.062277  14.726  < 2e-16 ***
## category_code_LT01_9_count  0.413106   0.228715   1.806  0.07150 .  
## category_code_LT01_10_count 0.087869   0.114965   0.764  0.44505    
## category_code_LT01_15_count 0.005749   0.759807   0.008  0.99397    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6238, Adjusted R-squared:  0.6192 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 0.619497306193294 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9899 -0.7592  0.0523  0.8877  3.3843 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96981    0.09076 109.854  < 2e-16 ***
## category_code_LT01_3_count   0.33101    0.11640   2.844  0.00465 ** 
## category_code_LT01_4_count   0.90863    0.08177  11.112  < 2e-16 ***
## category_code_LT01_5_count   0.91641    0.06225  14.722  < 2e-16 ***
## category_code_LT01_9_count   0.40970    0.22849   1.793  0.07358 .  
## category_code_LT01_10_count  0.08622    0.11472   0.752  0.45265    
## category_code_LT01_16_count  0.69183    1.17618   0.588  0.55667    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6241, Adjusted R-squared:  0.6195 
## F-statistic: 135.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.627559189763482 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0099 -0.7687  0.0535  0.8939  3.4399 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99318    0.08659 115.412  < 2e-16 ***
## category_code_LT01_3_count   0.25448    0.11653   2.184 0.029447 *  
## category_code_LT01_4_count   0.75194    0.09336   8.054  6.1e-15 ***
## category_code_LT01_5_count   0.91156    0.06184  14.740  < 2e-16 ***
## category_code_LT01_9_count   0.38217    0.22523   1.697 0.090368 .  
## category_code_LT01_11_count  0.38978    0.11704   3.330 0.000933 ***
## category_code_LT01_12_count -0.04027    0.21080  -0.191 0.848562    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6321, Adjusted R-squared:  0.6276 
## F-statistic: 140.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.62767205634366 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0080 -0.7536  0.0603  0.8891  3.4425 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99255    0.08656 115.442  < 2e-16 ***
## category_code_LT01_3_count   0.25346    0.11651   2.175 0.030072 *  
## category_code_LT01_4_count   0.74764    0.09379   7.971 1.11e-14 ***
## category_code_LT01_5_count   0.90979    0.06162  14.765  < 2e-16 ***
## category_code_LT01_9_count   0.38871    0.22566   1.723 0.085602 .  
## category_code_LT01_11_count  0.38100    0.11319   3.366 0.000822 ***
## category_code_LT01_13_count  0.10429    0.24224   0.431 0.667001    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6322, Adjusted R-squared:  0.6277 
## F-statistic: 140.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.627612120519247 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0086 -0.7549  0.0597  0.8994  3.4425 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99399    0.08663 115.359  < 2e-16 ***
## category_code_LT01_3_count   0.25637    0.11671   2.197 0.028509 *  
## category_code_LT01_4_count   0.74636    0.09473   7.879 2.14e-14 ***
## category_code_LT01_5_count   0.90850    0.06191  14.674  < 2e-16 ***
## category_code_LT01_9_count   0.37697    0.22583   1.669 0.095694 .  
## category_code_LT01_11_count  0.38268    0.11305   3.385 0.000769 ***
## category_code_LT01_14_count  0.10637    0.32625   0.326 0.744539    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6321, Adjusted R-squared:  0.6276 
## F-statistic: 140.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.627534513150087 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0088 -0.7604  0.0583  0.8965  3.4415 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99282    0.08657 115.426  < 2e-16 ***
## category_code_LT01_3_count   0.25505    0.11741   2.172 0.030304 *  
## category_code_LT01_4_count   0.75193    0.09347   8.045 6.54e-15 ***
## category_code_LT01_5_count   0.91044    0.06162  14.774  < 2e-16 ***
## category_code_LT01_9_count   0.38187    0.22540   1.694 0.090868 .  
## category_code_LT01_11_count  0.38420    0.11307   3.398 0.000734 ***
## category_code_LT01_15_count -0.04728    0.75036  -0.063 0.949789    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.632,  Adjusted R-squared:  0.6275 
## F-statistic: 140.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.62779664583869 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0088 -0.7558  0.0571  0.9003  3.4416 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99327    0.08654 115.470  < 2e-16 ***
## category_code_LT01_3_count   0.24622    0.11725   2.100 0.036236 *  
## category_code_LT01_4_count   0.75281    0.09334   8.066 5.63e-15 ***
## category_code_LT01_5_count   0.90990    0.06159  14.772  < 2e-16 ***
## category_code_LT01_9_count   0.37881    0.22523   1.682 0.093231 .  
## category_code_LT01_11_count  0.38350    0.11296   3.395 0.000742 ***
## category_code_LT01_16_count  0.68778    1.16294   0.591 0.554515    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6323, Adjusted R-squared:  0.6278 
## F-statistic: 140.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 0.619434154097385 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0032 -0.7758  0.0544  0.8913  3.4465 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98625    0.08751 114.122  < 2e-16 ***
## category_code_LT01_3_count   0.34534    0.11442   3.018  0.00268 ** 
## category_code_LT01_4_count   0.89368    0.08368  10.680  < 2e-16 ***
## category_code_LT01_5_count   0.91187    0.06253  14.582  < 2e-16 ***
## category_code_LT01_9_count   0.43798    0.22764   1.924  0.05494 .  
## category_code_LT01_12_count  0.13917    0.20580   0.676  0.49919    
## category_code_LT01_13_count  0.14887    0.24456   0.609  0.54300    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.624,  Adjusted R-squared:  0.6194 
## F-statistic: 135.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 0.619261371162911 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0041 -0.7776  0.0565  0.8892  3.4461 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98803    0.08760 114.016  < 2e-16 ***
## category_code_LT01_3_count   0.34979    0.11460   3.052  0.00239 ** 
## category_code_LT01_4_count   0.89437    0.08457  10.576  < 2e-16 ***
## category_code_LT01_5_count   0.91062    0.06280  14.500  < 2e-16 ***
## category_code_LT01_9_count   0.42287    0.22792   1.855  0.06415 .  
## category_code_LT01_12_count  0.13650    0.20640   0.661  0.50872    
## category_code_LT01_14_count  0.12703    0.33073   0.384  0.70107    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6239, Adjusted R-squared:  0.6193 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 0.619151224481821 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0043 -0.7762  0.0509  0.8925  3.4449 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98664    0.08754 114.084  < 2e-16 ***
## category_code_LT01_3_count   0.34607    0.11551   2.996  0.00287 ** 
## category_code_LT01_4_count   0.90037    0.08315  10.828  < 2e-16 ***
## category_code_LT01_5_count   0.91298    0.06255  14.597  < 2e-16 ***
## category_code_LT01_9_count   0.43011    0.22745   1.891  0.05922 .  
## category_code_LT01_12_count  0.14313    0.20585   0.695  0.48718    
## category_code_LT01_15_count  0.05618    0.75849   0.074  0.94099    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6192 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 0.619439122554164 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0042 -0.7766  0.0386  0.8964  3.4479 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98704    0.08751 114.130  < 2e-16 ***
## category_code_LT01_3_count   0.33875    0.11521   2.940  0.00343 ** 
## category_code_LT01_4_count   0.90183    0.08285  10.885  < 2e-16 ***
## category_code_LT01_5_count   0.91219    0.06252  14.590  < 2e-16 ***
## category_code_LT01_9_count   0.42563    0.22730   1.873  0.06173 .  
## category_code_LT01_12_count  0.14397    0.20572   0.700  0.48437    
## category_code_LT01_16_count  0.72198    1.17595   0.614  0.53953    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.624,  Adjusted R-squared:  0.6194 
## F-statistic: 135.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 0.619226459781646 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0064 -0.7752  0.0647  0.8783  3.4429 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98868    0.08759 114.034  < 2e-16 ***
## category_code_LT01_3_count   0.35421    0.11422   3.101  0.00204 ** 
## category_code_LT01_4_count   0.89506    0.08452  10.590  < 2e-16 ***
## category_code_LT01_5_count   0.91297    0.06261  14.582  < 2e-16 ***
## category_code_LT01_9_count   0.43233    0.22836   1.893  0.05891 .  
## category_code_LT01_13_count  0.15316    0.24453   0.626  0.53139    
## category_code_LT01_14_count  0.14344    0.32971   0.435  0.66372    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6238, Adjusted R-squared:  0.6192 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 0.619087461142068 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0069 -0.7745  0.0622  0.8850  3.4412 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98716    0.08754 114.090   <2e-16 ***
## category_code_LT01_3_count   0.35006    0.11519   3.039   0.0025 ** 
## category_code_LT01_4_count   0.90212    0.08293  10.878   <2e-16 ***
## category_code_LT01_5_count   0.91585    0.06231  14.698   <2e-16 ***
## category_code_LT01_9_count   0.44086    0.22792   1.934   0.0537 .  
## category_code_LT01_13_count  0.15527    0.24513   0.633   0.5268    
## category_code_LT01_15_count  0.07609    0.76007   0.100   0.9203    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 0.619386632842852 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0067 -0.7746  0.0600  0.8838  3.4417 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98756    0.08750 114.138  < 2e-16 ***
## category_code_LT01_3_count   0.34292    0.11489   2.985  0.00298 ** 
## category_code_LT01_4_count   0.90366    0.08259  10.942  < 2e-16 ***
## category_code_LT01_5_count   0.91500    0.06229  14.690  < 2e-16 ***
## category_code_LT01_9_count   0.43627    0.22771   1.916  0.05596 .  
## category_code_LT01_13_count  0.15890    0.24462   0.650  0.51626    
## category_code_LT01_16_count  0.74044    1.17668   0.629  0.52947    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.624,  Adjusted R-squared:  0.6194 
## F-statistic: 135.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 0.618924089660997 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0076 -0.7672  0.0549  0.8814  3.4411 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98909    0.08763 113.995  < 2e-16 ***
## category_code_LT01_3_count   0.35559    0.11530   3.084  0.00216 ** 
## category_code_LT01_4_count   0.90236    0.08389  10.756  < 2e-16 ***
## category_code_LT01_5_count   0.91419    0.06263  14.597  < 2e-16 ***
## category_code_LT01_9_count   0.42402    0.22819   1.858  0.06373 .  
## category_code_LT01_14_count  0.14400    0.32990   0.436  0.66267    
## category_code_LT01_15_count  0.03702    0.75865   0.049  0.96110    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6235, Adjusted R-squared:  0.6189 
## F-statistic: 135.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 0.619227887043194 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0075 -0.7668  0.0562  0.8821  3.4416 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98964    0.08760 114.042  < 2e-16 ***
## category_code_LT01_3_count   0.34788    0.11496   3.026  0.00261 ** 
## category_code_LT01_4_count   0.90321    0.08364  10.798  < 2e-16 ***
## category_code_LT01_5_count   0.91325    0.06260  14.589  < 2e-16 ***
## category_code_LT01_9_count   0.41916    0.22804   1.838  0.06665 .  
## category_code_LT01_14_count  0.15378    0.33005   0.466  0.64147    
## category_code_LT01_16_count  0.73920    1.17745   0.628  0.53043    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6238, Adjusted R-squared:  0.6192 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 0.619064973528135 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0080 -0.7682  0.0485  0.8850  3.4399 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98799    0.08754 114.095  < 2e-16 ***
## category_code_LT01_3_count   0.34408    0.11601   2.966  0.00316 ** 
## category_code_LT01_4_count   0.91102    0.08197  11.114  < 2e-16 ***
## category_code_LT01_5_count   0.91634    0.06230  14.709  < 2e-16 ***
## category_code_LT01_9_count   0.42808    0.22754   1.881  0.06052 .  
## category_code_LT01_15_count  0.06357    0.75906   0.084  0.93329    
## category_code_LT01_16_count  0.71841    1.17757   0.610  0.54209    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6237, Adjusted R-squared:  0.6191 
## F-statistic: 135.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.625986674668341 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9979 -0.7595  0.0498  0.8764  3.3376 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97623    0.08999 110.854  < 2e-16 ***
## category_code_LT01_3_count   0.26349    0.11744   2.243 0.025310 *  
## category_code_LT01_4_count   0.75990    0.09339   8.137 3.36e-15 ***
## category_code_LT01_5_count   0.91875    0.06182  14.860  < 2e-16 ***
## category_code_LT01_10_count  0.10139    0.11317   0.896 0.370738    
## category_code_LT01_11_count  0.40090    0.11707   3.424 0.000668 ***
## category_code_LT01_12_count -0.04844    0.21134  -0.229 0.818814    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.626012946165989 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9966 -0.7540  0.0545  0.8783  3.3415 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97605    0.08999 110.862  < 2e-16 ***
## category_code_LT01_3_count   0.26326    0.11744   2.242  0.02543 *  
## category_code_LT01_4_count   0.75699    0.09379   8.071 5.39e-15 ***
## category_code_LT01_5_count   0.91709    0.06160  14.887  < 2e-16 ***
## category_code_LT01_10_count  0.09966    0.11315   0.881  0.37887    
## category_code_LT01_11_count  0.39205    0.11320   3.463  0.00058 ***
## category_code_LT01_13_count  0.07150    0.24236   0.295  0.76812    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.625996567338295 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9980 -0.7490  0.0574  0.8807  3.3470 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97831    0.09043 110.339  < 2e-16 ***
## category_code_LT01_3_count   0.26595    0.11791   2.256 0.024538 *  
## category_code_LT01_4_count   0.75541    0.09478   7.970 1.12e-14 ***
## category_code_LT01_5_count   0.91581    0.06195  14.784  < 2e-16 ***
## category_code_LT01_10_count  0.09386    0.11610   0.808 0.419217    
## category_code_LT01_11_count  0.39290    0.11310   3.474 0.000558 ***
## category_code_LT01_14_count  0.08567    0.33468   0.256 0.798084    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.62597212977238 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9963 -0.7613  0.0506  0.8804  3.3394 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97564    0.09001 110.824  < 2e-16 ***
## category_code_LT01_3_count   0.26556    0.11812   2.248 0.024999 *  
## category_code_LT01_4_count   0.76034    0.09348   8.134 3.43e-15 ***
## category_code_LT01_5_count   0.91722    0.06161  14.887  < 2e-16 ***
## category_code_LT01_10_count  0.10181    0.11332   0.898 0.369389    
## category_code_LT01_11_count  0.39457    0.11309   3.489 0.000529 ***
## category_code_LT01_15_count -0.13764    0.75272  -0.183 0.854991    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.626231234331713 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9972 -0.7543  0.0552  0.8798  3.3422 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97682    0.08997 110.891  < 2e-16 ***
## category_code_LT01_3_count   0.25513    0.11815   2.159 0.031309 *  
## category_code_LT01_4_count   0.76074    0.09337   8.148  3.1e-15 ***
## category_code_LT01_5_count   0.91680    0.06158  14.888  < 2e-16 ***
## category_code_LT01_10_count  0.09864    0.11312   0.872 0.383624    
## category_code_LT01_11_count  0.39338    0.11300   3.481 0.000544 ***
## category_code_LT01_16_count  0.71255    1.16541   0.611 0.541207    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6307, Adjusted R-squared:  0.6262 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 0.617222329989916 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9919 -0.7586  0.0538  0.8803  3.3388 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96903    0.09102 109.529  < 2e-16 ***
## category_code_LT01_3_count   0.36114    0.11522   3.134  0.00182 ** 
## category_code_LT01_4_count   0.90976    0.08338  10.911  < 2e-16 ***
## category_code_LT01_5_count   0.92038    0.06256  14.713  < 2e-16 ***
## category_code_LT01_10_count  0.10515    0.11452   0.918  0.35897    
## category_code_LT01_12_count  0.13737    0.20651   0.665  0.50624    
## category_code_LT01_13_count  0.11391    0.24490   0.465  0.64205    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6172 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 0.61713560644993 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9938 -0.7615  0.0451  0.8805  3.3453 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97189    0.09149 108.994  < 2e-16 ***
## category_code_LT01_3_count   0.36513    0.11567   3.157  0.00169 ** 
## category_code_LT01_4_count   0.90939    0.08440  10.775  < 2e-16 ***
## category_code_LT01_5_count   0.91897    0.06287  14.616  < 2e-16 ***
## category_code_LT01_10_count  0.09807    0.11748   0.835  0.40422    
## category_code_LT01_12_count  0.13504    0.20702   0.652  0.51451    
## category_code_LT01_14_count  0.10999    0.33933   0.324  0.74597    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 0.617055854480798 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9921 -0.7584  0.0526  0.8822  3.3364 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96880    0.09106 109.474  < 2e-16 ***
## category_code_LT01_3_count   0.36255    0.11607   3.123  0.00189 ** 
## category_code_LT01_4_count   0.91526    0.08289  11.042  < 2e-16 ***
## category_code_LT01_5_count   0.92097    0.06257  14.719  < 2e-16 ***
## category_code_LT01_10_count  0.10698    0.11472   0.933  0.35152    
## category_code_LT01_12_count  0.13967    0.20655   0.676  0.49924    
## category_code_LT01_15_count -0.04022    0.76152  -0.053  0.95790    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 0.617370998948112 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9925 -0.7593  0.0530  0.8817  3.3389 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96977    0.09101 109.547  < 2e-16 ***
## category_code_LT01_3_count   0.35302    0.11601   3.043  0.00247 ** 
## category_code_LT01_4_count   0.91585    0.08263  11.083  < 2e-16 ***
## category_code_LT01_5_count   0.92023    0.06254  14.714  < 2e-16 ***
## category_code_LT01_10_count  0.10454    0.11450   0.913  0.36170    
## category_code_LT01_12_count  0.14131    0.20641   0.685  0.49392    
## category_code_LT01_16_count  0.75244    1.17916   0.638  0.52370    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 0.61698782364337 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9965 -0.7574  0.0621  0.8704  3.3417 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97276    0.09150 108.990  < 2e-16 ***
## category_code_LT01_3_count   0.37061    0.11531   3.214  0.00139 ** 
## category_code_LT01_4_count   0.91196    0.08428  10.821  < 2e-16 ***
## category_code_LT01_5_count   0.92167    0.06268  14.704  < 2e-16 ***
## category_code_LT01_10_count  0.09788    0.11753   0.833  0.40536    
## category_code_LT01_13_count  0.11894    0.24489   0.486  0.62740    
## category_code_LT01_14_count  0.12736    0.33849   0.376  0.70688    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616878540058993 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9947 -0.7588  0.0530  0.8684  3.3312 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96924    0.09108 109.453  < 2e-16 ***
## category_code_LT01_3_count   0.36755    0.11576   3.175  0.00159 ** 
## category_code_LT01_4_count   0.91905    0.08257  11.130  < 2e-16 ***
## category_code_LT01_5_count   0.92417    0.06233  14.826  < 2e-16 ***
## category_code_LT01_10_count  0.10816    0.11473   0.943  0.34625    
## category_code_LT01_13_count  0.11767    0.24547   0.479  0.63191    
## category_code_LT01_15_count -0.02939    0.76314  -0.039  0.96929    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6215, Adjusted R-squared:  0.6169 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617205993790698 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9951 -0.7598  0.0524  0.8694  3.3337 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97021    0.09103 109.529  < 2e-16 ***
## category_code_LT01_3_count   0.35808    0.11570   3.095  0.00208 ** 
## category_code_LT01_4_count   0.91954    0.08228  11.176  < 2e-16 ***
## category_code_LT01_5_count   0.92341    0.06230  14.821  < 2e-16 ***
## category_code_LT01_10_count  0.10573    0.11450   0.923  0.35625    
## category_code_LT01_13_count  0.12416    0.24498   0.507  0.61253    
## category_code_LT01_16_count  0.76619    1.18016   0.649  0.51649    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6172 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616807853029558 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9967 -0.7616  0.0558  0.8699  3.3389 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97246    0.09155 108.934  < 2e-16 ***
## category_code_LT01_3_count   0.37238    0.11614   3.206  0.00143 ** 
## category_code_LT01_4_count   0.91802    0.08369  10.970  < 2e-16 ***
## category_code_LT01_5_count   0.92234    0.06269  14.712  < 2e-16 ***
## category_code_LT01_10_count  0.10004    0.11771   0.850  0.39580    
## category_code_LT01_14_count  0.12629    0.33856   0.373  0.70929    
## category_code_LT01_15_count -0.05482    0.76150  -0.072  0.94264    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6168 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617134112324858 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9974 -0.7626  0.0506  0.8706  3.3423 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97380    0.09150 109.002  < 2e-16 ***
## category_code_LT01_3_count   0.36279    0.11603   3.127  0.00187 ** 
## category_code_LT01_4_count   0.91803    0.08346  11.000  < 2e-16 ***
## category_code_LT01_5_count   0.92144    0.06267  14.704  < 2e-16 ***
## category_code_LT01_10_count  0.09657    0.11755   0.822  0.41171    
## category_code_LT01_14_count  0.13748    0.33886   0.406  0.68513    
## category_code_LT01_16_count  0.76865    1.18101   0.651  0.51545    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617007127736759 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9954 -0.7595  0.0443  0.8789  3.3309 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96997    0.09108 109.467  < 2e-16 ***
## category_code_LT01_3_count   0.35979    0.11660   3.086  0.00214 ** 
## category_code_LT01_4_count   0.92558    0.08170  11.329  < 2e-16 ***
## category_code_LT01_5_count   0.92417    0.06232  14.830  < 2e-16 ***
## category_code_LT01_10_count  0.10773    0.11470   0.939  0.34808    
## category_code_LT01_15_count -0.03190    0.76211  -0.042  0.96663    
## category_code_LT01_16_count  0.74191    1.18091   0.628  0.53013    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.625454121185632 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0190 -0.7591  0.0484  0.8734  3.4281 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99760    0.08679 115.192  < 2e-16 ***
## category_code_LT01_3_count   0.28161    0.11574   2.433 0.015324 *  
## category_code_LT01_4_count   0.76037    0.09380   8.106 4.19e-15 ***
## category_code_LT01_5_count   0.91833    0.06188  14.839  < 2e-16 ***
## category_code_LT01_11_count  0.40039    0.11729   3.414 0.000694 ***
## category_code_LT01_12_count -0.04334    0.21141  -0.205 0.837644    
## category_code_LT01_13_count  0.07796    0.24248   0.322 0.747944    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6255 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.625540321996465 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0191 -0.7518  0.0500  0.8722  3.4290 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99936    0.08685 115.137  < 2e-16 ***
## category_code_LT01_3_count   0.28446    0.11587   2.455 0.014434 *  
## category_code_LT01_4_count   0.75549    0.09484   7.966 1.15e-14 ***
## category_code_LT01_5_count   0.91591    0.06217  14.733  < 2e-16 ***
## category_code_LT01_11_count  0.40128    0.11715   3.425 0.000665 ***
## category_code_LT01_12_count -0.04950    0.21191  -0.234 0.815386    
## category_code_LT01_14_count  0.15218    0.32711   0.465 0.641976    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6255 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.625389327535865 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0193 -0.7613  0.0469  0.8759  3.4277 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99769    0.08680 115.183  < 2e-16 ***
## category_code_LT01_3_count   0.28367    0.11658   2.433 0.015319 *  
## category_code_LT01_4_count   0.76382    0.09350   8.169 2.66e-15 ***
## category_code_LT01_5_count   0.91858    0.06189  14.842  < 2e-16 ***
## category_code_LT01_11_count  0.40296    0.11725   3.437 0.000639 ***
## category_code_LT01_12_count -0.04339    0.21153  -0.205 0.837570    
## category_code_LT01_15_count -0.10217    0.75238  -0.136 0.892040    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6254 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.625680823210436 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0193 -0.7495  0.0445  0.8762  3.4279 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99816    0.08677 115.233  < 2e-16 ***
## category_code_LT01_3_count   0.27299    0.11653   2.343 0.019551 *  
## category_code_LT01_4_count   0.76434    0.09337   8.186 2.35e-15 ***
## category_code_LT01_5_count   0.91798    0.06186  14.839  < 2e-16 ***
## category_code_LT01_11_count  0.40148    0.11711   3.428 0.000659 ***
## category_code_LT01_12_count -0.04083    0.21134  -0.193 0.846899    
## category_code_LT01_16_count  0.73813    1.16589   0.633 0.526964    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6257 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.625576771731743 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0174 -0.7502  0.0528  0.8650  3.4314 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99874    0.08682 115.164  < 2e-16 ***
## category_code_LT01_3_count   0.28380    0.11584   2.450 0.014639 *  
## category_code_LT01_4_count   0.75255    0.09525   7.901 1.83e-14 ***
## category_code_LT01_5_count   0.91429    0.06199  14.750  < 2e-16 ***
## category_code_LT01_11_count  0.39215    0.11333   3.460 0.000587 ***
## category_code_LT01_13_count  0.07756    0.24242   0.320 0.749132    
## category_code_LT01_14_count  0.14695    0.32624   0.450 0.652602    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6256 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.625430911006013 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0177 -0.7580  0.0505  0.8775  3.4299 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99719    0.08678 115.205  < 2e-16 ***
## category_code_LT01_3_count   0.28277    0.11656   2.426 0.015628 *  
## category_code_LT01_4_count   0.76061    0.09393   8.098 4.46e-15 ***
## category_code_LT01_5_count   0.91706    0.06167  14.870  < 2e-16 ***
## category_code_LT01_11_count  0.39460    0.11335   3.481 0.000543 ***
## category_code_LT01_13_count  0.07552    0.24301   0.311 0.756099    
## category_code_LT01_15_count -0.08118    0.75360  -0.108 0.914259    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6254 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.625741685400963 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0178 -0.7441  0.0474  0.8775  3.4301 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99765    0.08674 115.257  < 2e-16 ***
## category_code_LT01_3_count   0.27227    0.11651   2.337 0.019850 *  
## category_code_LT01_4_count   0.76103    0.09377   8.116  3.9e-15 ***
## category_code_LT01_5_count   0.91643    0.06164  14.868  < 2e-16 ***
## category_code_LT01_11_count  0.39338    0.11323   3.474 0.000558 ***
## category_code_LT01_13_count  0.08302    0.24252   0.342 0.732270    
## category_code_LT01_16_count  0.75537    1.16650   0.648 0.517575    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6257 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.625512797315427 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0176 -0.7549  0.0524  0.8736  3.4310 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99883    0.08683 115.155  < 2e-16 ***
## category_code_LT01_3_count   0.28587    0.11668   2.450 0.014638 *  
## category_code_LT01_4_count   0.75597    0.09493   7.963 1.18e-14 ***
## category_code_LT01_5_count   0.91452    0.06200  14.751  < 2e-16 ***
## category_code_LT01_11_count  0.39469    0.11322   3.486 0.000534 ***
## category_code_LT01_14_count  0.14737    0.32631   0.452 0.651736    
## category_code_LT01_15_count -0.10222    0.75191  -0.136 0.891922    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6255 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.625826506144784 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0177 -0.7427  0.0505  0.8735  3.4312 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99942    0.08680 115.207  < 2e-16 ***
## category_code_LT01_3_count   0.27503    0.11660   2.359  0.01873 *  
## category_code_LT01_4_count   0.75611    0.09481   7.975 1.08e-14 ***
## category_code_LT01_5_count   0.91379    0.06196  14.747  < 2e-16 ***
## category_code_LT01_11_count  0.39344    0.11312   3.478  0.00055 ***
## category_code_LT01_14_count  0.15605    0.32645   0.478  0.63285    
## category_code_LT01_16_count  0.76519    1.16670   0.656  0.51222    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6258 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.625660116271137 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0181 -0.7580  0.0444  0.8789  3.4296 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99776    0.08675 115.245  < 2e-16 ***
## category_code_LT01_3_count   0.27409    0.11741   2.334 0.019977 *  
## category_code_LT01_4_count   0.76448    0.09347   8.179 2.47e-15 ***
## category_code_LT01_5_count   0.91678    0.06165  14.871  < 2e-16 ***
## category_code_LT01_11_count  0.39596    0.11312   3.500 0.000507 ***
## category_code_LT01_15_count -0.07583    0.75241  -0.101 0.919769    
## category_code_LT01_16_count  0.73556    1.16700   0.630 0.528791    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6257 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616780684888298 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0137 -0.7578  0.0545  0.8765  3.4338 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99317    0.08784 113.765  < 2e-16 ***
## category_code_LT01_3_count   0.38319    0.11347   3.377 0.000791 ***
## category_code_LT01_4_count   0.90418    0.08519  10.614  < 2e-16 ***
## category_code_LT01_5_count   0.91710    0.06290  14.579  < 2e-16 ***
## category_code_LT01_12_count  0.13549    0.20715   0.654 0.513377    
## category_code_LT01_13_count  0.12039    0.24495   0.491 0.623307    
## category_code_LT01_14_count  0.17389    0.33085   0.526 0.599406    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6168 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.61656611822731 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0142 -0.7635  0.0473  0.8731  3.4320 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99135    0.08780 113.801  < 2e-16 ***
## category_code_LT01_3_count   0.37986    0.11442   3.320 0.000968 ***
## category_code_LT01_4_count   0.91321    0.08367  10.915  < 2e-16 ***
## category_code_LT01_5_count   0.92043    0.06263  14.697  < 2e-16 ***
## category_code_LT01_12_count  0.14434    0.20661   0.699 0.485123    
## category_code_LT01_13_count  0.12063    0.24553   0.491 0.623434    
## category_code_LT01_15_count  0.02787    0.76213   0.037 0.970844    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.616927767318628 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0140 -0.7581  0.0378  0.8738  3.4326 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99176    0.08776 113.859  < 2e-16 ***
## category_code_LT01_3_count   0.37056    0.11425   3.243  0.00126 ** 
## category_code_LT01_4_count   0.91409    0.08332  10.971  < 2e-16 ***
## category_code_LT01_5_count   0.91948    0.06260  14.689  < 2e-16 ***
## category_code_LT01_12_count  0.14532    0.20646   0.704  0.48185    
## category_code_LT01_13_count  0.12602    0.24506   0.514  0.60731    
## category_code_LT01_16_count  0.80464    1.18013   0.682  0.49567    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.6169 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616592176083334 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0144 -0.7693  0.0519  0.8712  3.4329 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.993368   0.087863 113.739  < 2e-16 ***
## category_code_LT01_3_count   0.384251   0.114514   3.355 0.000854 ***
## category_code_LT01_4_count   0.909759   0.084679  10.744  < 2e-16 ***
## category_code_LT01_5_count   0.917795   0.062922  14.586  < 2e-16 ***
## category_code_LT01_12_count  0.138325   0.207192   0.668 0.504691    
## category_code_LT01_14_count  0.173498   0.330991   0.524 0.600391    
## category_code_LT01_15_count -0.003819   0.760658  -0.005 0.995996    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.616960314821556 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0142 -0.7687  0.0412  0.8708  3.4335 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99392    0.08782 113.797  < 2e-16 ***
## category_code_LT01_3_count   0.37444    0.11431   3.276  0.00113 ** 
## category_code_LT01_4_count   0.91011    0.08442  10.781  < 2e-16 ***
## category_code_LT01_5_count   0.91675    0.06289  14.577  < 2e-16 ***
## category_code_LT01_12_count  0.13917    0.20703   0.672  0.50175    
## category_code_LT01_14_count  0.18320    0.33108   0.553  0.58027    
## category_code_LT01_16_count  0.81090    1.18040   0.687  0.49243    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.616722363660118 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0148 -0.7624  0.0309  0.8804  3.4315 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99198    0.08778 113.829  < 2e-16 ***
## category_code_LT01_3_count   0.37132    0.11535   3.219  0.00137 ** 
## category_code_LT01_4_count   0.91963    0.08284  11.102  < 2e-16 ***
## category_code_LT01_5_count   0.92028    0.06261  14.699  < 2e-16 ***
## category_code_LT01_12_count  0.14844    0.20650   0.719  0.47260    
## category_code_LT01_15_count  0.02617    0.76114   0.034  0.97258    
## category_code_LT01_16_count  0.78474    1.18085   0.665  0.50665    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6167 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616446888682849 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0172 -0.7625  0.0481  0.8660  3.4290 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.994218   0.087866 113.744  < 2e-16 ***
## category_code_LT01_3_count  0.389549   0.114106   3.414 0.000693 ***
## category_code_LT01_4_count  0.912142   0.084590  10.783  < 2e-16 ***
## category_code_LT01_5_count  0.920564   0.062729  14.675  < 2e-16 ***
## category_code_LT01_13_count 0.125066   0.245484   0.509 0.610654    
## category_code_LT01_14_count 0.191076   0.329990   0.579 0.562831    
## category_code_LT01_15_count 0.008414   0.762168   0.011 0.991196    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.616831176733969 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0170 -0.7716  0.0497  0.8638  3.4297 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99477    0.08782 113.805  < 2e-16 ***
## category_code_LT01_3_count   0.37975    0.11391   3.334 0.000922 ***
## category_code_LT01_4_count   0.91236    0.08429  10.824  < 2e-16 ***
## category_code_LT01_5_count   0.91945    0.06270  14.665  < 2e-16 ***
## category_code_LT01_13_count  0.13109    0.24500   0.535 0.592857    
## category_code_LT01_14_count  0.20120    0.33009   0.610 0.542449    
## category_code_LT01_16_count  0.82910    1.18135   0.702 0.483122    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6215, Adjusted R-squared:  0.6168 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.616543379473617 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0178 -0.7753  0.0340  0.8641  3.4271 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99271    0.08779 113.823  < 2e-16 ***
## category_code_LT01_3_count   0.37657    0.11499   3.275  0.00113 ** 
## category_code_LT01_4_count   0.92339    0.08251  11.191  < 2e-16 ***
## category_code_LT01_5_count   0.92363    0.06237  14.808  < 2e-16 ***
## category_code_LT01_13_count  0.13165    0.24564   0.536  0.59222    
## category_code_LT01_15_count  0.03997    0.76279   0.052  0.95823    
## category_code_LT01_16_count  0.80070    1.18196   0.677  0.49845    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6165 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.616607813083 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0178 -0.7645  0.0337  0.8640  3.4284 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.994999   0.087851 113.773  < 2e-16 ***
## category_code_LT01_3_count  0.381131   0.114989   3.314 0.000986 ***
## category_code_LT01_4_count  0.918537   0.083710  10.973  < 2e-16 ***
## category_code_LT01_5_count  0.920340   0.062715  14.675  < 2e-16 ***
## category_code_LT01_14_count 0.200819   0.330222   0.608 0.543380    
## category_code_LT01_15_count 0.005698   0.761110   0.007 0.994030    
## category_code_LT01_16_count 0.806703   1.182044   0.682 0.495267    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 0.600674984549784 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0753 -0.8209  0.0974  0.9199  3.7696 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.03134    0.08953 112.039  < 2e-16 ***
## category_code_LT01_3_count   0.53428    0.11256   4.747 2.72e-06 ***
## category_code_LT01_5_count   0.95081    0.06425  14.798  < 2e-16 ***
## category_code_LT01_6_count   0.62488    0.15327   4.077 5.32e-05 ***
## category_code_LT01_7_count   0.62192    0.15998   3.887 0.000115 ***
## category_code_LT01_8_count  -0.17247    0.28231  -0.611 0.541528    
## category_code_LT01_11_count  0.56806    0.11366   4.998 8.08e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.423 on 491 degrees of freedom
## Multiple R-squared:  0.6055, Adjusted R-squared:  0.6007 
## F-statistic: 125.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 0.602376193584573 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0611 -0.8329  0.0887  0.9372  3.7754 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.02558    0.08935 112.202  < 2e-16 ***
## category_code_LT01_3_count   0.50395    0.11371   4.432 1.15e-05 ***
## category_code_LT01_5_count   0.93871    0.06357  14.766  < 2e-16 ***
## category_code_LT01_6_count   0.60648    0.15305   3.963 8.51e-05 ***
## category_code_LT01_7_count   0.59227    0.16033   3.694 0.000245 ***
## category_code_LT01_9_count   0.36778    0.23375   1.573 0.116273    
## category_code_LT01_11_count  0.56240    0.11345   4.957 9.86e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.42 on 491 degrees of freedom
## Multiple R-squared:  0.6072, Adjusted R-squared:  0.6024 
## F-statistic: 126.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 0.600416907190466 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0644 -0.8302  0.0638  0.9223  3.7768 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.02417    0.09273 108.106  < 2e-16 ***
## category_code_LT01_3_count   0.52764    0.11427   4.617 4.97e-06 ***
## category_code_LT01_5_count   0.94541    0.06361  14.863  < 2e-16 ***
## category_code_LT01_6_count   0.61500    0.15500   3.968 8.34e-05 ***
## category_code_LT01_7_count   0.61476    0.16041   3.832 0.000143 ***
## category_code_LT01_10_count  0.02804    0.11863   0.236 0.813236    
## category_code_LT01_11_count  0.57190    0.11364   5.032 6.81e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.424 on 491 degrees of freedom
## Multiple R-squared:  0.6052, Adjusted R-squared:  0.6004 
## F-statistic: 125.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 0.600403459931646 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0709 -0.8263  0.0719  0.9251  3.7708 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.03015    0.08954 112.014  < 2e-16 ***
## category_code_LT01_3_count   0.53258    0.11256   4.732 2.92e-06 ***
## category_code_LT01_5_count   0.94619    0.06382  14.826  < 2e-16 ***
## category_code_LT01_6_count   0.62320    0.15371   4.054 5.84e-05 ***
## category_code_LT01_7_count   0.61611    0.16012   3.848 0.000135 ***
## category_code_LT01_11_count  0.57749    0.11807   4.891 1.36e-06 ***
## category_code_LT01_12_count -0.04352    0.21938  -0.198 0.842838    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.424 on 491 degrees of freedom
## Multiple R-squared:  0.6052, Adjusted R-squared:  0.6004 
## F-statistic: 125.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 0.600639963954152 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0685 -0.8413  0.0720  0.9337  3.7717 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.02922    0.08951 112.041  < 2e-16 ***
## category_code_LT01_3_count   0.53007    0.11258   4.708 3.26e-06 ***
## category_code_LT01_5_count   0.94407    0.06361  14.842  < 2e-16 ***
## category_code_LT01_6_count   0.62076    0.15312   4.054 5.85e-05 ***
## category_code_LT01_7_count   0.60629    0.16110   3.763 0.000188 ***
## category_code_LT01_11_count  0.56706    0.11378   4.984 8.65e-07 ***
## category_code_LT01_13_count  0.14433    0.25119   0.575 0.565835    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.423 on 491 degrees of freedom
## Multiple R-squared:  0.6055, Adjusted R-squared:  0.6006 
## F-statistic: 125.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 0.602560772601835 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0628 -0.8285  0.0918  0.9118  3.7686 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.03237    0.08930 112.340  < 2e-16 ***
## category_code_LT01_3_count   0.52846    0.11227   4.707 3.27e-06 ***
## category_code_LT01_5_count   0.93128    0.06398  14.555  < 2e-16 ***
## category_code_LT01_6_count   0.63304    0.15293   4.139 4.10e-05 ***
## category_code_LT01_7_count   0.59163    0.16026   3.692 0.000248 ***
## category_code_LT01_11_count  0.55072    0.11396   4.832 1.81e-06 ***
## category_code_LT01_14_count  0.54750    0.33291   1.645 0.100691    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.42 on 491 degrees of freedom
## Multiple R-squared:  0.6074, Adjusted R-squared:  0.6026 
## F-statistic: 126.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 0.600402860921286 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0701 -0.8257  0.0693  0.9324  3.7710 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.02996    0.08953 112.024  < 2e-16 ***
## category_code_LT01_3_count   0.52921    0.11366   4.656 4.15e-06 ***
## category_code_LT01_5_count   0.94541    0.06361  14.862  < 2e-16 ***
## category_code_LT01_6_count   0.61927    0.15332   4.039 6.22e-05 ***
## category_code_LT01_7_count   0.61883    0.15998   3.868 0.000124 ***
## category_code_LT01_11_count  0.56980    0.11379   5.008 7.70e-07 ***
## category_code_LT01_15_count  0.15267    0.77690   0.197 0.844296    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.424 on 491 degrees of freedom
## Multiple R-squared:  0.6052, Adjusted R-squared:  0.6004 
## F-statistic: 125.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_3_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 0.600935307806646 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0690 -0.8249  0.0835  0.9207  3.7710 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.03000    0.08947 112.101  < 2e-16 ***
## category_code_LT01_3_count   0.51977    0.11348   4.580 5.89e-06 ***
## category_code_LT01_5_count   0.94366    0.06358  14.842  < 2e-16 ***
## category_code_LT01_6_count   0.63108    0.15357   4.109 4.65e-05 ***
## category_code_LT01_7_count   0.61890    0.15980   3.873 0.000122 ***
## category_code_LT01_11_count  0.56873    0.11355   5.009 7.66e-07 ***
## category_code_LT01_16_count  1.00584    1.20759   0.833 0.405288    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.423 on 491 degrees of freedom
## Multiple R-squared:  0.6058, Adjusted R-squared:  0.6009 
## F-statistic: 125.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count 0.627422103123569 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9983 -0.7664  0.0037  0.9177  4.0567 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.98521    0.08667 115.208  < 2e-16 ***
## category_code_LT01_4_count  0.84918    0.08012  10.599  < 2e-16 ***
## category_code_LT01_5_count  0.90628    0.06250  14.501  < 2e-16 ***
## category_code_LT01_6_count  0.48382    0.14909   3.245  0.00125 ** 
## category_code_LT01_7_count  0.48894    0.15330   3.190  0.00152 ** 
## category_code_LT01_8_count -0.20855    0.27252  -0.765  0.44449    
## category_code_LT01_9_count  0.41805    0.22395   1.867  0.06254 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6319, Adjusted R-squared:  0.6274 
## F-statistic: 140.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count 0.6252151677489 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9910 -0.7604  0.0445  0.9208  3.9752 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97251    0.09012 110.652  < 2e-16 ***
## category_code_LT01_4_count   0.86637    0.07972  10.867  < 2e-16 ***
## category_code_LT01_5_count   0.91411    0.06255  14.613  < 2e-16 ***
## category_code_LT01_6_count   0.48418    0.15131   3.200 0.001464 ** 
## category_code_LT01_7_count   0.51003    0.15340   3.325 0.000951 ***
## category_code_LT01_8_count  -0.19729    0.27325  -0.722 0.470642    
## category_code_LT01_10_count  0.08574    0.11328   0.757 0.449481    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6297, Adjusted R-squared:  0.6252 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count 0.631238679879627 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0090 -0.7553  0.0271  0.9617  3.8156 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99404    0.08619 115.960  < 2e-16 ***
## category_code_LT01_4_count   0.73608    0.09123   8.068 5.52e-15 ***
## category_code_LT01_5_count   0.90908    0.06207  14.646  < 2e-16 ***
## category_code_LT01_6_count   0.41772    0.15082   2.770  0.00582 ** 
## category_code_LT01_7_count   0.39985    0.15704   2.546  0.01120 *  
## category_code_LT01_8_count  -0.16474    0.27121  -0.607  0.54385    
## category_code_LT01_11_count  0.33513    0.11426   2.933  0.00351 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6357, Adjusted R-squared:  0.6312 
## F-statistic: 142.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count 0.625004263832025 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0066 -0.7653  0.0347  0.9252  4.0517 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99018    0.08691 114.952  < 2e-16 ***
## category_code_LT01_4_count   0.86325    0.08065  10.704  < 2e-16 ***
## category_code_LT01_5_count   0.91110    0.06277  14.515  < 2e-16 ***
## category_code_LT01_6_count   0.49290    0.15045   3.276  0.00113 ** 
## category_code_LT01_7_count   0.51867    0.15291   3.392  0.00075 ***
## category_code_LT01_8_count  -0.19907    0.27344  -0.728  0.46694    
## category_code_LT01_12_count  0.11178    0.20531   0.544  0.58639    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6295, Adjusted R-squared:  0.625 
## F-statistic: 139.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count 0.624800004387154 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0086 -0.7680  0.0169  0.9169  4.0514 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99053    0.08693 114.926  < 2e-16 ***
## category_code_LT01_4_count   0.86889    0.08009  10.849  < 2e-16 ***
## category_code_LT01_5_count   0.91349    0.06262  14.589  < 2e-16 ***
## category_code_LT01_6_count   0.50364    0.14925   3.374 0.000798 ***
## category_code_LT01_7_count   0.51670    0.15408   3.354 0.000860 ***
## category_code_LT01_8_count  -0.19149    0.27390  -0.699 0.484797    
## category_code_LT01_13_count  0.04159    0.24446   0.170 0.864977    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count 0.624980676567906 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0082 -0.7625  0.0293  0.9222  4.0496 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99225    0.08696 114.904  < 2e-16 ***
## category_code_LT01_4_count   0.86149    0.08144  10.579  < 2e-16 ***
## category_code_LT01_5_count   0.91038    0.06293  14.468  < 2e-16 ***
## category_code_LT01_6_count   0.51029    0.14981   3.406 0.000713 ***
## category_code_LT01_7_count   0.51422    0.15329   3.355 0.000857 ***
## category_code_LT01_8_count  -0.19661    0.27334  -0.719 0.472321    
## category_code_LT01_14_count  0.16908    0.32814   0.515 0.606594    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6295, Adjusted R-squared:  0.625 
## F-statistic:   139 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count 0.624873323167473 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0093 -0.7689  0.0217  0.9075  4.0511 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99073    0.08692 114.944  < 2e-16 ***
## category_code_LT01_4_count   0.86636    0.08040  10.775  < 2e-16 ***
## category_code_LT01_5_count   0.91423    0.06259  14.606  < 2e-16 ***
## category_code_LT01_6_count   0.50051    0.14946   3.349 0.000874 ***
## category_code_LT01_7_count   0.52132    0.15297   3.408 0.000708 ***
## category_code_LT01_8_count  -0.19534    0.27336  -0.715 0.475213    
## category_code_LT01_15_count  0.26399    0.74692   0.353 0.723914    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6294, Adjusted R-squared:  0.6249 
## F-statistic:   139 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_16_count 0.626126991646204 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0068 -0.7655  0.0237  0.9243  4.0517 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99021    0.08677 115.130  < 2e-16 ***
## category_code_LT01_4_count   0.86138    0.07974  10.803  < 2e-16 ***
## category_code_LT01_5_count   0.91137    0.06250  14.581  < 2e-16 ***
## category_code_LT01_6_count   0.51594    0.14928   3.456 0.000595 ***
## category_code_LT01_7_count   0.51925    0.15266   3.401 0.000725 ***
## category_code_LT01_8_count  -0.21347    0.27327  -0.781 0.435074    
## category_code_LT01_16_count  1.54354    1.15962   1.331 0.183783    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6306, Adjusted R-squared:  0.6261 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count 0.627203962352045 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9791 -0.7577  0.0021  0.9183  4.0033 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97042    0.08986 110.954  < 2e-16 ***
## category_code_LT01_4_count   0.84753    0.08025  10.562  < 2e-16 ***
## category_code_LT01_5_count   0.89991    0.06189  14.541  < 2e-16 ***
## category_code_LT01_6_count   0.46634    0.15102   3.088  0.00213 ** 
## category_code_LT01_7_count   0.47949    0.15369   3.120  0.00192 ** 
## category_code_LT01_9_count   0.39952    0.22534   1.773  0.07685 .  
## category_code_LT01_10_count  0.06205    0.11368   0.546  0.58541    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6317, Adjusted R-squared:  0.6272 
## F-statistic: 140.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count 0.633048565045531 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9939 -0.7662  0.0280  0.9296  3.8289 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98749    0.08599 116.142  < 2e-16 ***
## category_code_LT01_4_count   0.72140    0.09138   7.895 1.92e-14 ***
## category_code_LT01_5_count   0.89664    0.06141  14.602  < 2e-16 ***
## category_code_LT01_6_count   0.39904    0.15055   2.651  0.00830 ** 
## category_code_LT01_7_count   0.37269    0.15715   2.372  0.01810 *  
## category_code_LT01_9_count   0.37204    0.22263   1.671  0.09534 .  
## category_code_LT01_11_count  0.32532    0.11414   2.850  0.00455 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.364 on 491 degrees of freedom
## Multiple R-squared:  0.6375, Adjusted R-squared:  0.633 
## F-statistic: 143.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count 0.627166506276007 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9895 -0.7680  0.0045  0.9246  4.0589 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98294    0.08667 115.179  < 2e-16 ***
## category_code_LT01_4_count   0.84330    0.08119  10.387  < 2e-16 ***
## category_code_LT01_5_count   0.89691    0.06210  14.442  < 2e-16 ***
## category_code_LT01_6_count   0.47004    0.15029   3.128  0.00187 ** 
## category_code_LT01_7_count   0.48455    0.15330   3.161  0.00167 ** 
## category_code_LT01_9_count   0.41178    0.22396   1.839  0.06657 .  
## category_code_LT01_12_count  0.10203    0.20463   0.499  0.61828    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6317, Adjusted R-squared:  0.6272 
## F-statistic: 140.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count 0.627068074711384 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9911 -0.7554  0.0048  0.9199  4.0588 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98312    0.08668 115.168  < 2e-16 ***
## category_code_LT01_4_count   0.84639    0.08075  10.482  < 2e-16 ***
## category_code_LT01_5_count   0.89894    0.06192  14.519  < 2e-16 ***
## category_code_LT01_6_count   0.47998    0.14907   3.220  0.00137 ** 
## category_code_LT01_7_count   0.47888    0.15456   3.098  0.00206 ** 
## category_code_LT01_9_count   0.41871    0.22452   1.865  0.06279 .  
## category_code_LT01_13_count  0.08410    0.24386   0.345  0.73033    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6316, Adjusted R-squared:  0.6271 
## F-statistic: 140.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count 0.627087283857417 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9913 -0.7546  0.0052  0.9174  4.0572 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98463    0.08674 115.111  < 2e-16 ***
## category_code_LT01_4_count   0.84348    0.08184  10.306  < 2e-16 ***
## category_code_LT01_5_count   0.89703    0.06223  14.414  < 2e-16 ***
## category_code_LT01_6_count   0.48496    0.14972   3.239  0.00128 ** 
## category_code_LT01_7_count   0.48186    0.15363   3.137  0.00181 ** 
## category_code_LT01_9_count   0.40743    0.22449   1.815  0.07015 .  
## category_code_LT01_14_count  0.12455    0.32794   0.380  0.70427    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6316, Adjusted R-squared:  0.6271 
## F-statistic: 140.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count 0.627086002070507 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9921 -0.7569 -0.0017  0.9131  4.0584 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98345    0.08668 115.179  < 2e-16 ***
## category_code_LT01_4_count   0.84537    0.08099  10.438  < 2e-16 ***
## category_code_LT01_5_count   0.89988    0.06190  14.537  < 2e-16 ***
## category_code_LT01_6_count   0.47648    0.14930   3.191  0.00151 ** 
## category_code_LT01_7_count   0.48703    0.15335   3.176  0.00159 ** 
## category_code_LT01_9_count   0.41465    0.22399   1.851  0.06474 .  
## category_code_LT01_15_count  0.28120    0.74477   0.378  0.70592    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6316, Adjusted R-squared:  0.6271 
## F-statistic: 140.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_16_count 0.628071401101371 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9897 -0.7559  0.0042  0.9149  4.0589 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98303    0.08656 115.326  < 2e-16 ***
## category_code_LT01_4_count   0.84236    0.08029  10.492  < 2e-16 ***
## category_code_LT01_5_count   0.89699    0.06185  14.503  < 2e-16 ***
## category_code_LT01_6_count   0.49123    0.14918   3.293  0.00106 ** 
## category_code_LT01_7_count   0.48579    0.15310   3.173  0.00160 ** 
## category_code_LT01_9_count   0.39940    0.22396   1.783  0.07515 .  
## category_code_LT01_16_count  1.38968    1.15654   1.202  0.23010    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6326, Adjusted R-squared:  0.6281 
## F-statistic: 140.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count 0.631329724218407 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9872 -0.7570  0.0178  0.9542  3.7465 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97589    0.08938 111.616  < 2e-16 ***
## category_code_LT01_4_count   0.73217    0.09132   8.017 7.96e-15 ***
## category_code_LT01_5_count   0.90382    0.06141  14.718  < 2e-16 ***
## category_code_LT01_6_count   0.39625    0.15267   2.595  0.00973 ** 
## category_code_LT01_7_count   0.38745    0.15738   2.462  0.01416 *  
## category_code_LT01_10_count  0.07868    0.11236   0.700  0.48412    
## category_code_LT01_11_count  0.33628    0.11419   2.945  0.00338 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6358, Adjusted R-squared:  0.6313 
## F-statistic: 142.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count 0.625008272658611 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9830 -0.7515  0.0310  0.9160  3.9799 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97084    0.09012 110.634  < 2e-16 ***
## category_code_LT01_4_count   0.86024    0.08080  10.647  < 2e-16 ***
## category_code_LT01_5_count   0.90497    0.06214  14.563  < 2e-16 ***
## category_code_LT01_6_count   0.47091    0.15242   3.090  0.00212 ** 
## category_code_LT01_7_count   0.50569    0.15339   3.297  0.00105 ** 
## category_code_LT01_10_count  0.08293    0.11335   0.732  0.46474    
## category_code_LT01_12_count  0.10267    0.20530   0.500  0.61724    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6295, Adjusted R-squared:  0.625 
## F-statistic: 139.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count 0.624846625352967 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9848 -0.7542  0.0221  0.9105  3.9786 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97097    0.09014 110.612  < 2e-16 ***
## category_code_LT01_4_count   0.86500    0.08025  10.779  < 2e-16 ***
## category_code_LT01_5_count   0.90735    0.06195  14.648  < 2e-16 ***
## category_code_LT01_6_count   0.48073    0.15131   3.177  0.00158 ** 
## category_code_LT01_7_count   0.50315    0.15447   3.257  0.00120 ** 
## category_code_LT01_10_count  0.08406    0.11336   0.742  0.45872    
## category_code_LT01_13_count  0.04783    0.24405   0.196  0.84469    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6294, Adjusted R-squared:  0.6248 
## F-statistic:   139 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count 0.624906651175078 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9863 -0.7491  0.0327  0.9121  3.9850 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97398    0.09056 110.131  < 2e-16 ***
## category_code_LT01_4_count   0.86108    0.08145  10.572  < 2e-16 ***
## category_code_LT01_5_count   0.90519    0.06233  14.524  < 2e-16 ***
## category_code_LT01_6_count   0.48699    0.15254   3.192  0.00150 ** 
## category_code_LT01_7_count   0.50386    0.15362   3.280  0.00111 ** 
## category_code_LT01_10_count  0.07547    0.11641   0.648  0.51707    
## category_code_LT01_14_count  0.11529    0.33707   0.342  0.73246    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6294, Adjusted R-squared:  0.6249 
## F-statistic:   139 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count 0.62488093453465 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9858 -0.7567  0.0241  0.9087  3.9802 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97157    0.09016 110.594  < 2e-16 ***
## category_code_LT01_4_count   0.86354    0.08052  10.724  < 2e-16 ***
## category_code_LT01_5_count   0.90792    0.06194  14.659  < 2e-16 ***
## category_code_LT01_6_count   0.47847    0.15142   3.160 0.001675 ** 
## category_code_LT01_7_count   0.50815    0.15348   3.311 0.000999 ***
## category_code_LT01_10_count  0.08201    0.11367   0.722 0.470936    
## category_code_LT01_15_count  0.21626    0.74917   0.289 0.772960    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6294, Adjusted R-squared:  0.6249 
## F-statistic:   139 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_16_count 0.626003210008191 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9842 -0.7497  0.0373  0.9075  3.9863 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97225    0.09001 110.790  < 2e-16 ***
## category_code_LT01_4_count   0.85870    0.07990  10.747  < 2e-16 ***
## category_code_LT01_5_count   0.90470    0.06188  14.620  < 2e-16 ***
## category_code_LT01_6_count   0.49362    0.15144   3.260  0.00119 ** 
## category_code_LT01_7_count   0.50679    0.15317   3.309  0.00101 ** 
## category_code_LT01_10_count  0.07584    0.11337   0.669  0.50382    
## category_code_LT01_16_count  1.44796    1.16043   1.248  0.21271    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count 0.631009234682745 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0050 -0.7470  0.0196  0.9587  3.8095 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99291    0.08619 115.942  < 2e-16 ***
## category_code_LT01_4_count   0.73560    0.09126   8.060 5.84e-15 ***
## category_code_LT01_5_count   0.90489    0.06164  14.680  < 2e-16 ***
## category_code_LT01_6_count   0.41666    0.15121   2.756  0.00608 ** 
## category_code_LT01_7_count   0.39390    0.15719   2.506  0.01254 *  
## category_code_LT01_11_count  0.34546    0.11829   2.920  0.00366 ** 
## category_code_LT01_12_count -0.05309    0.21082  -0.252  0.80126    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6355, Adjusted R-squared:  0.631 
## F-statistic: 142.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count 0.630972073518676 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0036 -0.7567  0.0294  0.9673  3.8156 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99250    0.08619 115.942  < 2e-16 ***
## category_code_LT01_4_count   0.73443    0.09156   8.022 7.72e-15 ***
## category_code_LT01_5_count   0.90347    0.06145  14.703  < 2e-16 ***
## category_code_LT01_6_count   0.41390    0.15074   2.746  0.00626 ** 
## category_code_LT01_7_count   0.39403    0.15788   2.496  0.01290 *  
## category_code_LT01_11_count  0.33727    0.11428   2.951  0.00332 ** 
## category_code_LT01_13_count  0.02862    0.24211   0.118  0.90594    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6354, Adjusted R-squared:  0.631 
## F-statistic: 142.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count 0.631099414558602 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0031 -0.7546  0.0411  0.9263  3.8148 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99387    0.08622 115.910  < 2e-16 ***
## category_code_LT01_4_count   0.72848    0.09262   7.865 2.37e-14 ***
## category_code_LT01_5_count   0.90074    0.06179  14.577  < 2e-16 ***
## category_code_LT01_6_count   0.41956    0.15134   2.772  0.00578 ** 
## category_code_LT01_7_count   0.39180    0.15726   2.491  0.01305 *  
## category_code_LT01_11_count  0.33639    0.11424   2.944  0.00339 ** 
## category_code_LT01_14_count  0.13943    0.32552   0.428  0.66860    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6356, Adjusted R-squared:  0.6311 
## F-statistic: 142.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count 0.630979363889037 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0039 -0.7435  0.0299  0.9685  3.8160 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99260    0.08618 115.947  < 2e-16 ***
## category_code_LT01_4_count   0.73402    0.09164   8.010  8.4e-15 ***
## category_code_LT01_5_count   0.90380    0.06145  14.709  < 2e-16 ***
## category_code_LT01_6_count   0.41262    0.15085   2.735  0.00646 ** 
## category_code_LT01_7_count   0.39706    0.15711   2.527  0.01181 *  
## category_code_LT01_11_count  0.33654    0.11447   2.940  0.00344 ** 
## category_code_LT01_15_count  0.11424    0.74240   0.154  0.87777    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.368 on 491 degrees of freedom
## Multiple R-squared:  0.6354, Adjusted R-squared:  0.631 
## F-statistic: 142.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_16_count 0.631939784492846 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0014 -0.7516  0.0412  0.9601  3.8207 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99198    0.08607 116.089  < 2e-16 ***
## category_code_LT01_4_count   0.73049    0.09124   8.007  8.6e-15 ***
## category_code_LT01_5_count   0.90108    0.06140  14.676  < 2e-16 ***
## category_code_LT01_6_count   0.42572    0.15090   2.821  0.00498 ** 
## category_code_LT01_7_count   0.39774    0.15677   2.537  0.01149 *  
## category_code_LT01_11_count  0.33060    0.11424   2.894  0.00397 ** 
## category_code_LT01_16_count  1.31449    1.15069   1.142  0.25387    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.366 on 491 degrees of freedom
## Multiple R-squared:  0.6364, Adjusted R-squared:  0.6319 
## F-statistic: 143.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count 0.62462951700135 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0001 -0.7467  0.0099  0.9279  4.0536 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98829    0.08692 114.916  < 2e-16 ***
## category_code_LT01_4_count   0.86217    0.08114  10.626  < 2e-16 ***
## category_code_LT01_5_count   0.90443    0.06218  14.545  < 2e-16 ***
## category_code_LT01_6_count   0.48960    0.15046   3.254 0.001216 ** 
## category_code_LT01_7_count   0.51159    0.15401   3.322 0.000961 ***
## category_code_LT01_12_count  0.10585    0.20540   0.515 0.606553    
## category_code_LT01_13_count  0.04842    0.24416   0.198 0.842887    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6292, Adjusted R-squared:  0.6246 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count 0.624761097561277 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9998 -0.7346  0.0204  0.9242  4.0520 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98985    0.08696 114.880  < 2e-16 ***
## category_code_LT01_4_count   0.85640    0.08229  10.407  < 2e-16 ***
## category_code_LT01_5_count   0.90173    0.06249  14.431  < 2e-16 ***
## category_code_LT01_6_count   0.49606    0.15116   3.282 0.001105 ** 
## category_code_LT01_7_count   0.51020    0.15327   3.329 0.000938 ***
## category_code_LT01_12_count  0.09876    0.20606   0.479 0.631946    
## category_code_LT01_14_count  0.15152    0.32945   0.460 0.645788    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count 0.624696577505383 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0006 -0.7431  0.0023  0.9179  4.0534 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98846    0.08691 114.930  < 2e-16 ***
## category_code_LT01_4_count   0.85969    0.08153  10.545  < 2e-16 ***
## category_code_LT01_5_count   0.90501    0.06217  14.556  < 2e-16 ***
## category_code_LT01_6_count   0.48607    0.15067   3.226 0.001339 ** 
## category_code_LT01_7_count   0.51663    0.15295   3.378 0.000789 ***
## category_code_LT01_12_count  0.10848    0.20533   0.528 0.597504    
## category_code_LT01_15_count  0.26635    0.74720   0.356 0.721646    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6292, Adjusted R-squared:  0.6247 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_16_count 0.625860471866177 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9977 -0.7365  0.0322  0.9263  4.0541 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98782    0.08677 115.100  < 2e-16 ***
## category_code_LT01_4_count   0.85534    0.08083  10.583  < 2e-16 ***
## category_code_LT01_5_count   0.90175    0.06211  14.518  < 2e-16 ***
## category_code_LT01_6_count   0.50110    0.15048   3.330 0.000934 ***
## category_code_LT01_7_count   0.51431    0.15266   3.369 0.000814 ***
## category_code_LT01_12_count  0.10453    0.20498   0.510 0.610321    
## category_code_LT01_16_count  1.49030    1.15848   1.286 0.198901    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6304, Adjusted R-squared:  0.6259 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count 0.624622191063939 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0016 -0.7403  0.0295  0.9189  4.0516 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99032    0.08697 114.873  < 2e-16 ***
## category_code_LT01_4_count   0.85999    0.08198  10.490  < 2e-16 ***
## category_code_LT01_5_count   0.90367    0.06234  14.497  < 2e-16 ***
## category_code_LT01_6_count   0.50640    0.14977   3.381 0.000779 ***
## category_code_LT01_7_count   0.50683    0.15441   3.282 0.001103 ** 
## category_code_LT01_13_count  0.05344    0.24407   0.219 0.826776    
## category_code_LT01_14_count  0.16609    0.32827   0.506 0.613123    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6292, Adjusted R-squared:  0.6246 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count 0.624525174108632 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0027 -0.7590  0.0164  0.9113  4.0530 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98883    0.08693 114.913  < 2e-16 ***
## category_code_LT01_4_count   0.86449    0.08102  10.670  < 2e-16 ***
## category_code_LT01_5_count   0.90749    0.06198  14.642  < 2e-16 ***
## category_code_LT01_6_count   0.49674    0.14942   3.324 0.000952 ***
## category_code_LT01_7_count   0.51359    0.15405   3.334 0.000921 ***
## category_code_LT01_13_count  0.05728    0.24451   0.234 0.814890    
## category_code_LT01_15_count  0.26889    0.74852   0.359 0.719577    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6291, Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_16_count 0.62571331691632 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9997 -0.7519  0.0265  0.9203  4.0537 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98815    0.08679 115.086  < 2e-16 ***
## category_code_LT01_4_count   0.85962    0.08031  10.704  < 2e-16 ***
## category_code_LT01_5_count   0.90406    0.06192  14.601  < 2e-16 ***
## category_code_LT01_6_count   0.51159    0.14925   3.428 0.000660 ***
## category_code_LT01_7_count   0.51076    0.15378   3.321 0.000963 ***
## category_code_LT01_13_count  0.06307    0.24384   0.259 0.796019    
## category_code_LT01_16_count  1.50631    1.15935   1.299 0.194462    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6302, Adjusted R-squared:  0.6257 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count 0.624672324315354 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0022 -0.7513  0.0196  0.9114  4.0514 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99049    0.08696 114.885  < 2e-16 ***
## category_code_LT01_4_count   0.85824    0.08223  10.438  < 2e-16 ***
## category_code_LT01_5_count   0.90439    0.06233  14.510  < 2e-16 ***
## category_code_LT01_6_count   0.50312    0.14999   3.354 0.000857 ***
## category_code_LT01_7_count   0.51230    0.15334   3.341 0.000899 ***
## category_code_LT01_14_count  0.16328    0.32828   0.497 0.619139    
## category_code_LT01_15_count  0.25177    0.74720   0.337 0.736303    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6292, Adjusted R-squared:  0.6247 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_16_count 0.625914370730453 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9991 -0.7349  0.0431  0.9160  4.0518 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99005    0.08682 115.070  < 2e-16 ***
## category_code_LT01_4_count   0.85182    0.08169  10.427  < 2e-16 ***
## category_code_LT01_5_count   0.90044    0.06227  14.460  < 2e-16 ***
## category_code_LT01_6_count   0.51897    0.14982   3.464 0.000579 ***
## category_code_LT01_7_count   0.50913    0.15304   3.327 0.000944 ***
## category_code_LT01_14_count  0.18875    0.32817   0.575 0.565439    
## category_code_LT01_16_count  1.53202    1.16004   1.321 0.187231    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6304, Adjusted R-squared:  0.6259 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_7_count+category_code_LT01_15_count+category_code_LT01_16_count 0.625770699246897 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0004 -0.7577  0.0292  0.9138  4.0535 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98838    0.08678 115.099  < 2e-16 ***
## category_code_LT01_4_count   0.85762    0.08061  10.639  < 2e-16 ***
## category_code_LT01_5_count   0.90481    0.06191  14.616  < 2e-16 ***
## category_code_LT01_6_count   0.50804    0.14944   3.400 0.000730 ***
## category_code_LT01_7_count   0.51703    0.15271   3.386 0.000767 ***
## category_code_LT01_15_count  0.28138    0.74619   0.377 0.706273    
## category_code_LT01_16_count  1.50621    1.15889   1.300 0.194314    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6303, Adjusted R-squared:  0.6258 
## F-statistic: 139.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 0.620171101905003 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9863 -0.7731  0.0472  0.9518  3.9775 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96655    0.09071 109.870  < 2e-16 ***
## category_code_LT01_4_count   0.94387    0.07476  12.625  < 2e-16 ***
## category_code_LT01_5_count   0.91596    0.06304  14.530  < 2e-16 ***
## category_code_LT01_6_count   0.46979    0.15253   3.080  0.00219 ** 
## category_code_LT01_8_count  -0.18685    0.27508  -0.679  0.49729    
## category_code_LT01_9_count   0.47424    0.22641   2.095  0.03672 *  
## category_code_LT01_10_count  0.08907    0.11445   0.778  0.43682    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6248, Adjusted R-squared:  0.6202 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 0.629089406896759 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0042 -0.7621  0.0410  0.9446  3.7806 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98977    0.08649 115.506  < 2e-16 ***
## category_code_LT01_4_count   0.76661    0.08995   8.522  < 2e-16 ***
## category_code_LT01_5_count   0.90827    0.06233  14.573  < 2e-16 ***
## category_code_LT01_6_count   0.38973    0.15139   2.574 0.010335 *  
## category_code_LT01_8_count  -0.15456    0.27194  -0.568 0.570054    
## category_code_LT01_9_count   0.42327    0.22307   1.897 0.058357 .  
## category_code_LT01_11_count  0.39163    0.11110   3.525 0.000463 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.372 on 491 degrees of freedom
## Multiple R-squared:  0.6336, Adjusted R-squared:  0.6291 
## F-statistic: 141.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 0.619945107958319 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0022 -0.7775  0.0407  0.9308  4.0572 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98467    0.08754 114.057  < 2e-16 ***
## category_code_LT01_4_count   0.94130    0.07573  12.430  < 2e-16 ***
## category_code_LT01_5_count   0.91266    0.06325  14.429  < 2e-16 ***
## category_code_LT01_6_count   0.47812    0.15181   3.149  0.00174 ** 
## category_code_LT01_8_count  -0.18892    0.27527  -0.686  0.49285    
## category_code_LT01_9_count   0.49355    0.22488   2.195  0.02865 *  
## category_code_LT01_12_count  0.11569    0.20669   0.560  0.57593    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6245, Adjusted R-squared:  0.6199 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 0.620082539655644 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0027 -0.7740  0.0289  0.9102  4.0574 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98449    0.08753 114.075  < 2e-16 ***
## category_code_LT01_4_count   0.93920    0.07577  12.396  < 2e-16 ***
## category_code_LT01_5_count   0.91369    0.06309  14.481  < 2e-16 ***
## category_code_LT01_6_count   0.48924    0.15055   3.250  0.00123 ** 
## category_code_LT01_8_count  -0.17329    0.27551  -0.629  0.52967    
## category_code_LT01_9_count   0.50394    0.22515   2.238  0.02565 *  
## category_code_LT01_13_count  0.17135    0.24453   0.701  0.48381    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6247, Adjusted R-squared:  0.6201 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 0.619971222205135 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0038 -0.7767  0.0185  0.9273  4.0548 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98710    0.08760 114.012  < 2e-16 ***
## category_code_LT01_4_count   0.93786    0.07682  12.209  < 2e-16 ***
## category_code_LT01_5_count   0.91157    0.06340  14.378  < 2e-16 ***
## category_code_LT01_6_count   0.49722    0.15122   3.288  0.00108 ** 
## category_code_LT01_8_count  -0.18661    0.27516  -0.678  0.49797    
## category_code_LT01_9_count   0.48531    0.22549   2.152  0.03186 *  
## category_code_LT01_14_count  0.19464    0.33040   0.589  0.55606    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:   0.62 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 0.619774578422417 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0049 -0.7748  0.0325  0.9361  4.0567 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98519    0.08756 114.043  < 2e-16 ***
## category_code_LT01_4_count   0.94553    0.07533  12.552  < 2e-16 ***
## category_code_LT01_5_count   0.91583    0.06308  14.518  < 2e-16 ***
## category_code_LT01_6_count   0.48638    0.15084   3.224  0.00135 ** 
## category_code_LT01_8_count  -0.18487    0.27521  -0.672  0.50207    
## category_code_LT01_9_count   0.49664    0.22495   2.208  0.02772 *  
## category_code_LT01_15_count  0.22920    0.75186   0.305  0.76061    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6244, Adjusted R-squared:  0.6198 
## F-statistic:   136 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 0.620858192667815 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0030 -0.7783  0.0322  0.9333  4.0570 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98491    0.08743 114.202  < 2e-16 ***
## category_code_LT01_4_count   0.94129    0.07468  12.604  < 2e-16 ***
## category_code_LT01_5_count   0.91345    0.06300  14.499  < 2e-16 ***
## category_code_LT01_6_count   0.50121    0.15073   3.325 0.000949 ***
## category_code_LT01_8_count  -0.20126    0.27517  -0.731 0.464885    
## category_code_LT01_9_count   0.48150    0.22487   2.141 0.032745 *  
## category_code_LT01_16_count  1.43034    1.16923   1.223 0.221796    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6254, Adjusted R-squared:  0.6209 
## F-statistic: 136.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 0.626983302729911 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9941 -0.7529 -0.0114  0.9305  3.6745 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97403    0.08992 110.925  < 2e-16 ***
## category_code_LT01_4_count   0.78022    0.08985   8.684  < 2e-16 ***
## category_code_LT01_5_count   0.91635    0.06236  14.694  < 2e-16 ***
## category_code_LT01_6_count   0.38318    0.15355   2.496 0.012904 *  
## category_code_LT01_8_count  -0.14149    0.27259  -0.519 0.603953    
## category_code_LT01_10_count  0.10128    0.11269   0.899 0.369246    
## category_code_LT01_11_count  0.40697    0.11103   3.665 0.000274 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6315, Adjusted R-squared:  0.627 
## F-statistic: 140.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 0.617019725232878 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9909 -0.7769  0.0014  0.9189  3.9480 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96662    0.09109 109.418  < 2e-16 ***
## category_code_LT01_4_count   0.96587    0.07496  12.885  < 2e-16 ***
## category_code_LT01_5_count   0.92247    0.06335  14.562  < 2e-16 ***
## category_code_LT01_6_count   0.47568    0.15411   3.087  0.00214 ** 
## category_code_LT01_8_count  -0.17482    0.27624  -0.633  0.52712    
## category_code_LT01_10_count  0.11583    0.11415   1.015  0.31074    
## category_code_LT01_12_count  0.11574    0.20756   0.558  0.57736    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 0.617005852814232 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9921 -0.7800  0.0329  0.9081  3.9481 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96675    0.09109 109.417  < 2e-16 ***
## category_code_LT01_4_count   0.96653    0.07482  12.918  < 2e-16 ***
## category_code_LT01_5_count   0.92406    0.06319  14.625  < 2e-16 ***
## category_code_LT01_6_count   0.48720    0.15297   3.185  0.00154 ** 
## category_code_LT01_8_count  -0.16127    0.27657  -0.583  0.56009    
## category_code_LT01_10_count  0.11559    0.11417   1.012  0.31183    
## category_code_LT01_13_count  0.13281    0.24529   0.541  0.58846    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 0.616991375660817 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9951 -0.7787  0.0400  0.8918  3.9569 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97143    0.09153 108.936  < 2e-16 ***
## category_code_LT01_4_count   0.96376    0.07600  12.681  < 2e-16 ***
## category_code_LT01_5_count   0.92154    0.06355  14.501  < 2e-16 ***
## category_code_LT01_6_count   0.49655    0.15424   3.219  0.00137 ** 
## category_code_LT01_8_count  -0.17207    0.27614  -0.623  0.53350    
## category_code_LT01_10_count  0.10338    0.11734   0.881  0.37875    
## category_code_LT01_14_count  0.17823    0.34015   0.524  0.60052    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 0.616803476093567 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9935 -0.7863  0.0136  0.8928  3.9472 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96709    0.09114 109.364  < 2e-16 ***
## category_code_LT01_4_count   0.97157    0.07444  13.052  < 2e-16 ***
## category_code_LT01_5_count   0.92554    0.06317  14.651  < 2e-16 ***
## category_code_LT01_6_count   0.48501    0.15313   3.167  0.00163 ** 
## category_code_LT01_8_count  -0.17035    0.27619  -0.617  0.53765    
## category_code_LT01_10_count  0.11614    0.11446   1.015  0.31075    
## category_code_LT01_15_count  0.13887    0.75681   0.183  0.85449    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6168 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 0.61802537598987 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9928 -0.7901  0.0024  0.9180  3.9541 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96816    0.09098 109.570  < 2e-16 ***
## category_code_LT01_4_count   0.96522    0.07391  13.059  < 2e-16 ***
## category_code_LT01_5_count   0.92292    0.06309  14.629  < 2e-16 ***
## category_code_LT01_6_count   0.50023    0.15316   3.266  0.00117 ** 
## category_code_LT01_8_count  -0.18804    0.27611  -0.681  0.49617    
## category_code_LT01_10_count  0.10888    0.11416   0.954  0.34069    
## category_code_LT01_16_count  1.48746    1.17431   1.267  0.20588    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 0.626471348721602 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0170 -0.7383  0.0113  0.9565  3.7536 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99595    0.08675 115.231  < 2e-16 ***
## category_code_LT01_4_count   0.78561    0.08971   8.757  < 2e-16 ***
## category_code_LT01_5_count   0.91782    0.06257  14.668  < 2e-16 ***
## category_code_LT01_6_count   0.40955    0.15220   2.691 0.007370 ** 
## category_code_LT01_8_count  -0.13306    0.27296  -0.487 0.626148    
## category_code_LT01_11_count  0.42171    0.11486   3.671 0.000268 ***
## category_code_LT01_12_count -0.07748    0.21197  -0.366 0.714866    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.631,  Adjusted R-squared:  0.6265 
## F-statistic: 139.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 0.626467497587391 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0146 -0.7565  0.0187  0.9601  3.7635 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99523    0.08674 115.228  < 2e-16 ***
## category_code_LT01_4_count   0.78214    0.09023   8.669  < 2e-16 ***
## category_code_LT01_5_count   0.91540    0.06244  14.660  < 2e-16 ***
## category_code_LT01_6_count   0.40607    0.15173   2.676 0.007695 ** 
## category_code_LT01_8_count  -0.13165    0.27316  -0.482 0.630053    
## category_code_LT01_11_count  0.40851    0.11123   3.673 0.000266 ***
## category_code_LT01_13_count  0.08697    0.24255   0.359 0.720089    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.631,  Adjusted R-squared:  0.6265 
## F-statistic: 139.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 0.626636893802857 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0145 -0.7639  0.0297  0.9215  3.7618 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99732    0.08677 115.213  < 2e-16 ***
## category_code_LT01_4_count   0.77539    0.09133   8.490 2.46e-16 ***
## category_code_LT01_5_count   0.91215    0.06276  14.535  < 2e-16 ***
## category_code_LT01_6_count   0.41362    0.15236   2.715 0.006866 ** 
## category_code_LT01_8_count  -0.14025    0.27273  -0.514 0.607299    
## category_code_LT01_11_count  0.40796    0.11111   3.672 0.000267 ***
## category_code_LT01_14_count  0.19378    0.32690   0.593 0.553605    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6311, Adjusted R-squared:  0.6266 
## F-statistic:   140 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 0.626371758558708 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0155 -0.7574  0.0224  0.9586  3.7617 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99553    0.08675 115.222  < 2e-16 ***
## category_code_LT01_4_count   0.78520    0.09004   8.721  < 2e-16 ***
## category_code_LT01_5_count   0.91623    0.06243  14.676  < 2e-16 ***
## category_code_LT01_6_count   0.40474    0.15187   2.665 0.007950 ** 
## category_code_LT01_8_count  -0.13726    0.27279  -0.503 0.615059    
## category_code_LT01_11_count  0.41061    0.11122   3.692 0.000248 ***
## category_code_LT01_15_count  0.03884    0.74639   0.052 0.958519    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6309, Adjusted R-squared:  0.6264 
## F-statistic: 139.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 0.627356658411451 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0136 -0.7564  0.0288  0.9505  3.7668 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99508    0.08664 115.368  < 2e-16 ***
## category_code_LT01_4_count   0.78109    0.08969   8.709  < 2e-16 ***
## category_code_LT01_5_count   0.91421    0.06236  14.661  < 2e-16 ***
## category_code_LT01_6_count   0.41764    0.15193   2.749 0.006200 ** 
## category_code_LT01_8_count  -0.15399    0.27282  -0.564 0.572702    
## category_code_LT01_11_count  0.40393    0.11106   3.637 0.000305 ***
## category_code_LT01_16_count  1.32224    1.15949   1.140 0.254690    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6319, Adjusted R-squared:  0.6274 
## F-statistic: 140.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 0.616459269230541 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0140 -0.7920  0.0259  0.9361  4.0512 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99072    0.08789 113.667  < 2e-16 ***
## category_code_LT01_4_count   0.96677    0.07566  12.777  < 2e-16 ***
## category_code_LT01_5_count   0.92101    0.06343  14.520  < 2e-16 ***
## category_code_LT01_6_count   0.50224    0.15214   3.301  0.00103 ** 
## category_code_LT01_8_count  -0.16138    0.27688  -0.583  0.56026    
## category_code_LT01_12_count  0.11821    0.20773   0.569  0.56956    
## category_code_LT01_13_count  0.13681    0.24546   0.557  0.57754    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6165 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 0.616600389402518 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0143 -0.7891  0.0292  0.9153  4.0485 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99338    0.08793 113.647  < 2e-16 ***
## category_code_LT01_4_count   0.96065    0.07691  12.491  < 2e-16 ***
## category_code_LT01_5_count   0.91762    0.06372  14.401  < 2e-16 ***
## category_code_LT01_6_count   0.51185    0.15285   3.349 0.000874 ***
## category_code_LT01_8_count  -0.17337    0.27639  -0.627 0.530765    
## category_code_LT01_12_count  0.10921    0.20838   0.524 0.600464    
## category_code_LT01_14_count  0.23290    0.33221   0.701 0.483596    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 0.616274778580574 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0155 -0.7940  0.0177  0.9333  4.0507 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99119    0.08791 113.649  < 2e-16 ***
## category_code_LT01_4_count   0.97077    0.07543  12.869  < 2e-16 ***
## category_code_LT01_5_count   0.92252    0.06342  14.546  < 2e-16 ***
## category_code_LT01_6_count   0.49896    0.15242   3.274  0.00114 ** 
## category_code_LT01_8_count  -0.17114    0.27648  -0.619  0.53622    
## category_code_LT01_12_count  0.12318    0.20771   0.593  0.55342    
## category_code_LT01_15_count  0.20607    0.75532   0.273  0.78510    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.6163 
## F-statistic:   134 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 0.617578052823862 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0131 -0.7958  0.0193  0.9455  4.0512 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99070    0.08776 113.836  < 2e-16 ***
## category_code_LT01_4_count   0.96470    0.07482  12.894  < 2e-16 ***
## category_code_LT01_5_count   0.91978    0.06333  14.524  < 2e-16 ***
## category_code_LT01_6_count   0.51410    0.15222   3.377  0.00079 ***
## category_code_LT01_8_count  -0.18953    0.27638  -0.686  0.49319    
## category_code_LT01_12_count  0.11985    0.20732   0.578  0.56346    
## category_code_LT01_16_count  1.55062    1.17283   1.322  0.18675    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6176 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616646103416439 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0152 -0.7831  0.0333  0.9016  4.0483 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99354    0.08792 113.661  < 2e-16 ***
## category_code_LT01_4_count   0.95947    0.07706  12.451  < 2e-16 ***
## category_code_LT01_5_count   0.91864    0.06360  14.445  < 2e-16 ***
## category_code_LT01_6_count   0.52335    0.15142   3.456 0.000595 ***
## category_code_LT01_8_count  -0.15978    0.27669  -0.577 0.563897    
## category_code_LT01_13_count  0.14158    0.24526   0.577 0.564024    
## category_code_LT01_14_count  0.24835    0.33090   0.751 0.453292    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616275010707084 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0168 -0.7808  0.0220  0.9034  4.0506 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99127    0.08791 113.651  < 2e-16 ***
## category_code_LT01_4_count   0.97096    0.07538  12.881  < 2e-16 ***
## category_code_LT01_5_count   0.92421    0.06326  14.611  < 2e-16 ***
## category_code_LT01_6_count   0.51098    0.15113   3.381  0.00078 ***
## category_code_LT01_8_count  -0.15650    0.27679  -0.565  0.57206    
## category_code_LT01_13_count  0.14586    0.24584   0.593  0.55325    
## category_code_LT01_15_count  0.22434    0.75658   0.297  0.76696    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.6163 
## F-statistic:   134 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617615664857154 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0142 -0.7820  0.0196  0.9440  4.0512 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99073    0.08776 113.843  < 2e-16 ***
## category_code_LT01_4_count   0.96446    0.07472  12.907  < 2e-16 ***
## category_code_LT01_5_count   0.92125    0.06316  14.585  < 2e-16 ***
## category_code_LT01_6_count   0.52625    0.15095   3.486 0.000534 ***
## category_code_LT01_8_count  -0.17494    0.27666  -0.632 0.527452    
## category_code_LT01_13_count  0.15157    0.24507   0.618 0.536539    
## category_code_LT01_16_count  1.57838    1.17330   1.345 0.179166    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6176 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616434244894781 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0168 -0.7836  0.0389  0.9034  4.0478 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99403    0.08795 113.639  < 2e-16 ***
## category_code_LT01_4_count   0.96441    0.07668  12.578  < 2e-16 ***
## category_code_LT01_5_count   0.92032    0.06359  14.473  < 2e-16 ***
## category_code_LT01_6_count   0.52066    0.15169   3.432 0.000649 ***
## category_code_LT01_8_count  -0.16955    0.27633  -0.614 0.539774    
## category_code_LT01_14_count  0.24684    0.33104   0.746 0.456239    
## category_code_LT01_15_count  0.18780    0.75511   0.249 0.803694    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617847377391285 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0142 -0.7833  0.0340  0.9299  4.0481 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99376    0.08778 113.846  < 2e-16 ***
## category_code_LT01_4_count   0.95594    0.07625  12.536  < 2e-16 ***
## category_code_LT01_5_count   0.91689    0.06350  14.440  < 2e-16 ***
## category_code_LT01_6_count   0.53680    0.15152   3.543 0.000434 ***
## category_code_LT01_8_count  -0.18927    0.27621  -0.685 0.493515    
## category_code_LT01_14_count  0.27294    0.33088   0.825 0.409824    
## category_code_LT01_16_count  1.60892    1.17414   1.370 0.171221    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6178 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617384781568217 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0160 -0.7809  0.0267  0.9338  4.0506 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99128    0.08778 113.819  < 2e-16 ***
## category_code_LT01_4_count   0.96945    0.07436  13.036  < 2e-16 ***
## category_code_LT01_5_count   0.92307    0.06315  14.617  < 2e-16 ***
## category_code_LT01_6_count   0.52309    0.15120   3.460 0.000588 ***
## category_code_LT01_8_count  -0.18532    0.27633  -0.671 0.502746    
## category_code_LT01_15_count  0.22122    0.75429   0.293 0.769431    
## category_code_LT01_16_count  1.56431    1.17343   1.333 0.183116    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.629191428494852 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9836 -0.7573  0.0154  0.9693  3.7140 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97242    0.08963 111.264  < 2e-16 ***
## category_code_LT01_4_count   0.76234    0.09006   8.465 2.97e-16 ***
## category_code_LT01_5_count   0.90355    0.06167  14.652  < 2e-16 ***
## category_code_LT01_6_count   0.37016    0.15307   2.418 0.015956 *  
## category_code_LT01_9_count   0.40120    0.22446   1.787 0.074486 .  
## category_code_LT01_10_count  0.07657    0.11312   0.677 0.498782    
## category_code_LT01_11_count  0.39141    0.11108   3.524 0.000465 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6337, Adjusted R-squared:  0.6292 
## F-statistic: 141.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 0.620020505044022 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9786 -0.7546  0.0269  0.9382  3.9820 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96501    0.09071 109.860  < 2e-16 ***
## category_code_LT01_4_count   0.93695    0.07596  12.335  < 2e-16 ***
## category_code_LT01_5_count   0.90708    0.06263  14.484  < 2e-16 ***
## category_code_LT01_6_count   0.45654    0.15362   2.972  0.00311 ** 
## category_code_LT01_9_count   0.46840    0.22638   2.069  0.03906 *  
## category_code_LT01_10_count  0.08634    0.11451   0.754  0.45121    
## category_code_LT01_12_count  0.10670    0.20665   0.516  0.60584    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:   0.62 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 0.620200003998086 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9798 -0.7548  0.0323  0.9141  3.9835 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96526    0.09068 109.889  < 2e-16 ***
## category_code_LT01_4_count   0.93429    0.07598  12.297  < 2e-16 ***
## category_code_LT01_5_count   0.90838    0.06242  14.553  < 2e-16 ***
## category_code_LT01_6_count   0.46747    0.15244   3.067  0.00228 ** 
## category_code_LT01_9_count   0.47948    0.22673   2.115  0.03495 *  
## category_code_LT01_10_count  0.08475    0.11453   0.740  0.45967    
## category_code_LT01_13_count  0.17255    0.24431   0.706  0.48036    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6248, Adjusted R-squared:  0.6202 
## F-statistic: 136.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 0.619947326151473 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9823 -0.7609  0.0362  0.9263  3.9885 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96884    0.09116 109.361  < 2e-16 ***
## category_code_LT01_4_count   0.93650    0.07685  12.186  < 2e-16 ***
## category_code_LT01_5_count   0.90689    0.06280  14.440  < 2e-16 ***
## category_code_LT01_6_count   0.47457    0.15380   3.086  0.00215 ** 
## category_code_LT01_9_count   0.46508    0.22666   2.052  0.04071 *  
## category_code_LT01_10_count  0.07699    0.11754   0.655  0.51277    
## category_code_LT01_14_count  0.14069    0.33921   0.415  0.67850    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6245, Adjusted R-squared:  0.6199 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 0.619858215978146 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9813 -0.7625  0.0465  0.9245  3.9819 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96562    0.09075 109.816  < 2e-16 ***
## category_code_LT01_4_count   0.94134    0.07553  12.463  < 2e-16 ***
## category_code_LT01_5_count   0.91007    0.06242  14.579  < 2e-16 ***
## category_code_LT01_6_count   0.46469    0.15264   3.044  0.00246 ** 
## category_code_LT01_9_count   0.47127    0.22650   2.081  0.03798 *  
## category_code_LT01_10_count  0.08589    0.11484   0.748  0.45488    
## category_code_LT01_15_count  0.17985    0.75407   0.239  0.81159    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6244, Adjusted R-squared:  0.6199 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 0.620828209409534 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9801 -0.7575  0.0511  0.9285  3.9869 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96632    0.09062 109.985  < 2e-16 ***
## category_code_LT01_4_count   0.93715    0.07493  12.507  < 2e-16 ***
## category_code_LT01_5_count   0.90737    0.06237  14.548  < 2e-16 ***
## category_code_LT01_6_count   0.47900    0.15271   3.137  0.00181 ** 
## category_code_LT01_9_count   0.45813    0.22635   2.024  0.04351 *  
## category_code_LT01_10_count  0.08066    0.11452   0.704  0.48156    
## category_code_LT01_16_count  1.34025    1.16960   1.146  0.25239    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6254, Adjusted R-squared:  0.6208 
## F-statistic: 136.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.628949387849983 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0011 -0.7716  0.0240  0.9499  3.7726 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98893    0.08648 115.503  < 2e-16 ***
## category_code_LT01_4_count   0.76570    0.08995   8.512  < 2e-16 ***
## category_code_LT01_5_count   0.90500    0.06188  14.624  < 2e-16 ***
## category_code_LT01_6_count   0.39078    0.15181   2.574  0.01034 *  
## category_code_LT01_9_count   0.41828    0.22300   1.876  0.06129 .  
## category_code_LT01_11_count  0.40444    0.11486   3.521  0.00047 ***
## category_code_LT01_12_count -0.07831    0.21110  -0.371  0.71082    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.372 on 491 degrees of freedom
## Multiple R-squared:  0.6334, Adjusted R-squared:  0.6289 
## F-statistic: 141.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.629038541302392 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9982 -0.7553  0.0378  0.9563  3.7837 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98800    0.08647 115.513  < 2e-16 ***
## category_code_LT01_4_count   0.76051    0.09051   8.402 4.75e-16 ***
## category_code_LT01_5_count   0.90221    0.06171  14.621  < 2e-16 ***
## category_code_LT01_6_count   0.38746    0.15129   2.561 0.010735 *  
## category_code_LT01_9_count   0.42603    0.22340   1.907 0.057096 .  
## category_code_LT01_11_count  0.38974    0.11131   3.501 0.000505 ***
## category_code_LT01_13_count  0.12227    0.24181   0.506 0.613346    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.372 on 491 degrees of freedom
## Multiple R-squared:  0.6335, Adjusted R-squared:  0.629 
## F-statistic: 141.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.628998680728315 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9987 -0.7556  0.0353  0.9569  3.7805 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98989    0.08653 115.456  < 2e-16 ***
## category_code_LT01_4_count   0.75819    0.09145   8.291 1.09e-15 ***
## category_code_LT01_5_count   0.90019    0.06203  14.511  < 2e-16 ***
## category_code_LT01_6_count   0.39283    0.15201   2.584 0.010046 *  
## category_code_LT01_9_count   0.41172    0.22355   1.842 0.066122 .  
## category_code_LT01_11_count  0.39166    0.11114   3.524 0.000465 ***
## category_code_LT01_14_count  0.14713    0.32665   0.450 0.652607    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.372 on 491 degrees of freedom
## Multiple R-squared:  0.6335, Adjusted R-squared:  0.629 
## F-statistic: 141.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.628851878629556 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9994 -0.7660  0.0421  0.9605  3.7810 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98845    0.08648 115.496  < 2e-16 ***
## category_code_LT01_4_count   0.76491    0.09030   8.470 2.86e-16 ***
## category_code_LT01_5_count   0.90327    0.06171  14.639  < 2e-16 ***
## category_code_LT01_6_count   0.38551    0.15146   2.545 0.011222 *  
## category_code_LT01_9_count   0.41948    0.22308   1.880 0.060646 .  
## category_code_LT01_11_count  0.39297    0.11128   3.531 0.000452 ***
## category_code_LT01_15_count  0.06896    0.74409   0.093 0.926198    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.372 on 491 degrees of freedom
## Multiple R-squared:  0.6333, Adjusted R-squared:  0.6289 
## F-statistic: 141.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.629641468578712 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9976 -0.7545  0.0474  0.9644  3.7849 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98806    0.08639 115.613  < 2e-16 ***
## category_code_LT01_4_count   0.76196    0.08994   8.472 2.83e-16 ***
## category_code_LT01_5_count   0.90112    0.06166  14.614  < 2e-16 ***
## category_code_LT01_6_count   0.39744    0.15155   2.623 0.008998 ** 
## category_code_LT01_9_count   0.40818    0.22303   1.830 0.067826 .  
## category_code_LT01_11_count  0.38793    0.11110   3.492 0.000523 ***
## category_code_LT01_16_count  1.18708    1.15551   1.027 0.304772    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.371 on 491 degrees of freedom
## Multiple R-squared:  0.6341, Adjusted R-squared:  0.6296 
## F-statistic: 141.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 0.619981733133562 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9948 -0.7720  0.0314  0.9150  4.0594 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98249    0.08751 114.076  < 2e-16 ***
## category_code_LT01_4_count   0.93189    0.07689  12.119  < 2e-16 ***
## category_code_LT01_5_count   0.90523    0.06265  14.449  < 2e-16 ***
## category_code_LT01_6_count   0.47571    0.15173   3.135  0.00182 ** 
## category_code_LT01_9_count   0.49803    0.22513   2.212  0.02741 *  
## category_code_LT01_12_count  0.10644    0.20668   0.515  0.60678    
## category_code_LT01_13_count  0.17589    0.24430   0.720  0.47188    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:   0.62 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 0.619800749520036 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9958 -0.7744  0.0503  0.9479  4.0570 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98484    0.08759 113.994  < 2e-16 ***
## category_code_LT01_4_count   0.93213    0.07776  11.988  < 2e-16 ***
## category_code_LT01_5_count   0.90320    0.06296  14.346  < 2e-16 ***
## category_code_LT01_6_count   0.48312    0.15257   3.167  0.00164 ** 
## category_code_LT01_9_count   0.47983    0.22545   2.128  0.03381 *  
## category_code_LT01_12_count  0.10152    0.20742   0.489  0.62473    
## category_code_LT01_14_count  0.17689    0.33171   0.533  0.59407    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6244, Adjusted R-squared:  0.6198 
## F-statistic:   136 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 0.619654433806478 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9966 -0.7779  0.0413  0.9327  4.0588 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98308    0.08754 114.038  < 2e-16 ***
## category_code_LT01_4_count   0.93803    0.07659  12.248  < 2e-16 ***
## category_code_LT01_5_count   0.90688    0.06266  14.473  < 2e-16 ***
## category_code_LT01_6_count   0.47201    0.15205   3.104  0.00202 ** 
## category_code_LT01_9_count   0.49012    0.22490   2.179  0.02978 *  
## category_code_LT01_12_count  0.11246    0.20671   0.544  0.58666    
## category_code_LT01_15_count  0.23230    0.75209   0.309  0.75755    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6242, Adjusted R-squared:  0.6197 
## F-statistic:   136 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 0.620660713113722 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9943 -0.7722  0.0431  0.9437  4.0592 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98268    0.08743 114.184  < 2e-16 ***
## category_code_LT01_4_count   0.93432    0.07590  12.310  < 2e-16 ***
## category_code_LT01_5_count   0.90414    0.06260  14.443  < 2e-16 ***
## category_code_LT01_6_count   0.48645    0.15191   3.202  0.00145 ** 
## category_code_LT01_9_count   0.47510    0.22486   2.113  0.03512 *  
## category_code_LT01_12_count  0.10903    0.20640   0.528  0.59756    
## category_code_LT01_16_count  1.38114    1.16805   1.182  0.23761    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6252, Adjusted R-squared:  0.6207 
## F-statistic: 136.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 0.620033888093685 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9964 -0.7724  0.0330  0.9053  4.0570 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98484    0.08756 114.036  < 2e-16 ***
## category_code_LT01_4_count   0.92787    0.07803  11.891  < 2e-16 ***
## category_code_LT01_5_count   0.90403    0.06279  14.397  < 2e-16 ***
## category_code_LT01_6_count   0.49382    0.15110   3.268  0.00116 ** 
## category_code_LT01_9_count   0.49011    0.22573   2.171  0.03039 *  
## category_code_LT01_13_count  0.17959    0.24416   0.736  0.46237    
## category_code_LT01_14_count  0.19053    0.33034   0.577  0.56436    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:   0.62 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 0.619868646228183 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9974 -0.7725  0.0273  0.8972  4.0589 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98298    0.08752 114.070  < 2e-16 ***
## category_code_LT01_4_count   0.93454    0.07670  12.184  < 2e-16 ***
## category_code_LT01_5_count   0.90826    0.06245  14.544  < 2e-16 ***
## category_code_LT01_6_count   0.48286    0.15072   3.204  0.00145 ** 
## category_code_LT01_9_count   0.50174    0.22519   2.228  0.02633 *  
## category_code_LT01_13_count  0.18520    0.24470   0.757  0.44950    
## category_code_LT01_15_count  0.25992    0.75321   0.345  0.73018    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6245, Adjusted R-squared:  0.6199 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 0.620908611020936 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9949 -0.7712  0.0288  0.9033  4.0593 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98254    0.08740 114.221  < 2e-16 ***
## category_code_LT01_4_count   0.93061    0.07597  12.250  < 2e-16 ***
## category_code_LT01_5_count   0.90530    0.06239  14.509  < 2e-16 ***
## category_code_LT01_6_count   0.49758    0.15060   3.304  0.00102 ** 
## category_code_LT01_9_count   0.48636    0.22510   2.161  0.03121 *  
## category_code_LT01_13_count  0.18905    0.24400   0.775  0.43883    
## category_code_LT01_16_count  1.41460    1.16818   1.211  0.22650    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.6209 
## F-statistic: 136.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 0.619679426060973 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9982 -0.7750  0.0382  0.9182  4.0564 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98546    0.08760 113.994  < 2e-16 ***
## category_code_LT01_4_count   0.93491    0.07758  12.051  < 2e-16 ***
## category_code_LT01_5_count   0.90586    0.06280  14.424  < 2e-16 ***
## category_code_LT01_6_count   0.49080    0.15142   3.241  0.00127 ** 
## category_code_LT01_9_count   0.48207    0.22552   2.138  0.03304 *  
## category_code_LT01_14_count  0.18938    0.33054   0.573  0.56695    
## category_code_LT01_15_count  0.21649    0.75203   0.288  0.77357    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6243, Adjusted R-squared:  0.6197 
## F-statistic:   136 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 0.620770116264852 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9957 -0.7748  0.0375  0.9258  4.0566 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98529    0.08747 114.156  < 2e-16 ***
## category_code_LT01_4_count   0.92906    0.07708  12.053  < 2e-16 ***
## category_code_LT01_5_count   0.90246    0.06275  14.382  < 2e-16 ***
## category_code_LT01_6_count   0.50621    0.15132   3.345 0.000885 ***
## category_code_LT01_9_count   0.46529    0.22550   2.063 0.039606 *  
## category_code_LT01_14_count  0.21443    0.33057   0.649 0.516849    
## category_code_LT01_16_count  1.43042    1.16979   1.223 0.221989    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6253, Adjusted R-squared:  0.6208 
## F-statistic: 136.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 0.620527000928462 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9970 -0.7805  0.0286  0.9174  4.0587 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98321    0.08744 114.176  < 2e-16 ***
## category_code_LT01_4_count   0.93781    0.07553  12.416  < 2e-16 ***
## category_code_LT01_5_count   0.90726    0.06240  14.539  < 2e-16 ***
## category_code_LT01_6_count   0.49411    0.15090   3.274  0.00113 ** 
## category_code_LT01_9_count   0.47813    0.22491   2.126  0.03401 *  
## category_code_LT01_15_count  0.24454    0.75127   0.325  0.74494    
## category_code_LT01_16_count  1.39522    1.16851   1.194  0.23305    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6251, Adjusted R-squared:  0.6205 
## F-statistic: 136.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.626903069273991 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9914 -0.7352 -0.0078  0.9307  3.6660 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97330    0.08991 110.928  < 2e-16 ***
## category_code_LT01_4_count   0.77919    0.08984   8.673  < 2e-16 ***
## category_code_LT01_5_count   0.91358    0.06189  14.762  < 2e-16 ***
## category_code_LT01_6_count   0.38482    0.15391   2.500 0.012733 *  
## category_code_LT01_10_count  0.10119    0.11271   0.898 0.369732    
## category_code_LT01_11_count  0.42043    0.11478   3.663 0.000276 ***
## category_code_LT01_12_count -0.08568    0.21172  -0.405 0.685880    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6314, Adjusted R-squared:  0.6269 
## F-statistic: 140.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.626876346750394 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9894 -0.7444 -0.0035  0.9339  3.6786 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97301    0.08991 110.925  < 2e-16 ***
## category_code_LT01_4_count   0.77586    0.09032   8.590  < 2e-16 ***
## category_code_LT01_5_count   0.91101    0.06172  14.761  < 2e-16 ***
## category_code_LT01_6_count   0.38137    0.15349   2.485 0.013303 *  
## category_code_LT01_10_count  0.09897    0.11275   0.878 0.380477    
## category_code_LT01_11_count  0.40617    0.11121   3.652 0.000288 ***
## category_code_LT01_13_count  0.08684    0.24216   0.359 0.720042    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6314, Adjusted R-squared:  0.6269 
## F-statistic: 140.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.626892468385715 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9912 -0.7535 -0.0081  0.9368  3.6847 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97638    0.09033 110.439  < 2e-16 ***
## category_code_LT01_4_count   0.77290    0.09130   8.465 2.97e-16 ***
## category_code_LT01_5_count   0.90883    0.06211  14.634  < 2e-16 ***
## category_code_LT01_6_count   0.38791    0.15481   2.506 0.012542 *  
## category_code_LT01_10_count  0.08982    0.11586   0.775 0.438578    
## category_code_LT01_11_count  0.40704    0.11108   3.664 0.000275 ***
## category_code_LT01_14_count  0.13002    0.33591   0.387 0.698874    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6314, Adjusted R-squared:  0.6269 
## F-statistic: 140.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.626778895159716 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9897 -0.7448 -0.0102  0.9378  3.6753 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97295    0.08994 110.885  < 2e-16 ***
## category_code_LT01_4_count   0.77934    0.09014   8.646  < 2e-16 ***
## category_code_LT01_5_count   0.91157    0.06172  14.770  < 2e-16 ***
## category_code_LT01_6_count   0.38005    0.15354   2.475 0.013648 *  
## category_code_LT01_10_count  0.10039    0.11301   0.888 0.374810    
## category_code_LT01_11_count  0.40873    0.11118   3.676 0.000263 ***
## category_code_LT01_15_count -0.01422    0.74798  -0.019 0.984839    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6313, Adjusted R-squared:  0.6268 
## F-statistic: 140.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.627631174406663 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9891 -0.7529  0.0064  0.9363  3.6867 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97396    0.08982 111.042  < 2e-16 ***
## category_code_LT01_4_count   0.77528    0.08983   8.631  < 2e-16 ***
## category_code_LT01_5_count   0.90924    0.06167  14.743  < 2e-16 ***
## category_code_LT01_6_count   0.39282    0.15377   2.555 0.010931 *  
## category_code_LT01_10_count  0.09306    0.11278   0.825 0.409706    
## category_code_LT01_11_count  0.40254    0.11104   3.625 0.000319 ***
## category_code_LT01_16_count  1.22932    1.15944   1.060 0.289545    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6321, Adjusted R-squared:  0.6276 
## F-statistic: 140.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 0.616952176849523 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9851 -0.7625 -0.0017  0.9137  3.9528 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96541    0.09107 109.424   <2e-16 ***
## category_code_LT01_4_count   0.95896    0.07597  12.623   <2e-16 ***
## category_code_LT01_5_count   0.91584    0.06272  14.601   <2e-16 ***
## category_code_LT01_6_count   0.47416    0.15407   3.078   0.0022 ** 
## category_code_LT01_10_count  0.11260    0.11421   0.986   0.3247    
## category_code_LT01_12_count  0.10809    0.20756   0.521   0.6028    
## category_code_LT01_13_count  0.13726    0.24501   0.560   0.5756    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 0.616880836417137 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9876 -0.7608  0.0098  0.9128  3.9604 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96955    0.09153 108.926  < 2e-16 ***
## category_code_LT01_4_count   0.95766    0.07696  12.443  < 2e-16 ***
## category_code_LT01_5_count   0.91349    0.06309  14.480  < 2e-16 ***
## category_code_LT01_6_count   0.48269    0.15554   3.103  0.00202 ** 
## category_code_LT01_10_count  0.10185    0.11736   0.868  0.38589    
## category_code_LT01_12_count  0.10338    0.20822   0.496  0.61977    
## category_code_LT01_14_count  0.16097    0.34135   0.472  0.63745    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6215, Adjusted R-squared:  0.6169 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 0.616735692676746 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9861 -0.7657 -0.0050  0.9180  3.9520 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96569    0.09112 109.368  < 2e-16 ***
## category_code_LT01_4_count   0.96386    0.07571  12.731  < 2e-16 ***
## category_code_LT01_5_count   0.91694    0.06273  14.617  < 2e-16 ***
## category_code_LT01_6_count   0.47131    0.15424   3.056  0.00237 ** 
## category_code_LT01_10_count  0.11302    0.11451   0.987  0.32415    
## category_code_LT01_12_count  0.11247    0.20758   0.542  0.58821    
## category_code_LT01_15_count  0.14432    0.75705   0.191  0.84889    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6167 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 0.617882272029367 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9849 -0.7614  0.0049  0.9300  3.9588 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96657    0.09097 109.563  < 2e-16 ***
## category_code_LT01_4_count   0.95800    0.07515  12.748  < 2e-16 ***
## category_code_LT01_5_count   0.91390    0.06267  14.583  < 2e-16 ***
## category_code_LT01_6_count   0.48606    0.15425   3.151  0.00173 ** 
## category_code_LT01_10_count  0.10602    0.11423   0.928  0.35376    
## category_code_LT01_12_count  0.10961    0.20722   0.529  0.59710    
## category_code_LT01_16_count  1.44127    1.17299   1.229  0.21977    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6179 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616952177425453 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9892 -0.7598  0.0082  0.8959  3.9618 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97020    0.09151 108.949  < 2e-16 ***
## category_code_LT01_4_count   0.95615    0.07709  12.403  < 2e-16 ***
## category_code_LT01_5_count   0.91480    0.06292  14.538  < 2e-16 ***
## category_code_LT01_6_count   0.49437    0.15416   3.207  0.00143 ** 
## category_code_LT01_10_count  0.10005    0.11741   0.852  0.39458    
## category_code_LT01_13_count  0.14238    0.24491   0.581  0.56126    
## category_code_LT01_14_count  0.17713    0.34015   0.521  0.60279    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 0.61677703438123 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9878 -0.7686 -0.0066  0.9018  3.9524 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96598    0.09112 109.377  < 2e-16 ***
## category_code_LT01_4_count   0.96346    0.07563  12.739  < 2e-16 ***
## category_code_LT01_5_count   0.91885    0.06252  14.697  < 2e-16 ***
## category_code_LT01_6_count   0.48273    0.15305   3.154  0.00171 ** 
## category_code_LT01_10_count  0.11241    0.11453   0.981  0.32684    
## category_code_LT01_13_count  0.14450    0.24546   0.589  0.55635    
## category_code_LT01_15_count  0.16378    0.75838   0.216  0.82910    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6168 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617965185942663 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9864 -0.7634 -0.0020  0.9183  3.9594 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96684    0.09096 109.577  < 2e-16 ***
## category_code_LT01_4_count   0.95710    0.07504  12.755  < 2e-16 ***
## category_code_LT01_5_count   0.91558    0.06246  14.659  < 2e-16 ***
## category_code_LT01_6_count   0.49774    0.15308   3.252  0.00123 ** 
## category_code_LT01_10_count  0.10529    0.11424   0.922  0.35716    
## category_code_LT01_13_count  0.15213    0.24473   0.622  0.53450    
## category_code_LT01_16_count  1.47229    1.17359   1.255  0.21025    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616713565209807 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9903 -0.7683 -0.0004  0.9035  3.9606 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97041    0.09156 108.890  < 2e-16 ***
## category_code_LT01_4_count   0.96182    0.07670  12.540  < 2e-16 ***
## category_code_LT01_5_count   0.91608    0.06293  14.557  < 2e-16 ***
## category_code_LT01_6_count   0.49183    0.15432   3.187  0.00153 ** 
## category_code_LT01_10_count  0.10088    0.11770   0.857  0.39182    
## category_code_LT01_14_count  0.17521    0.34024   0.515  0.60682    
## category_code_LT01_15_count  0.13563    0.75688   0.179  0.85786    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6213, Adjusted R-squared:  0.6167 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617947967011204 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9893 -0.7658  0.0090  0.9111  3.9698 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97216    0.09141 109.095  < 2e-16 ***
## category_code_LT01_4_count   0.95371    0.07631  12.499  < 2e-16 ***
## category_code_LT01_5_count   0.91221    0.06288  14.507  < 2e-16 ***
## category_code_LT01_6_count   0.50850    0.15443   3.293  0.00106 ** 
## category_code_LT01_10_count  0.09096    0.11753   0.774  0.43935    
## category_code_LT01_14_count  0.20551    0.34053   0.604  0.54644    
## category_code_LT01_16_count  1.49586    1.17575   1.272  0.20389    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.6179 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617700175386851 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9876 -0.7750 -0.0052  0.9097  3.9584 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.96714    0.09101 109.514  < 2e-16 ***
## category_code_LT01_4_count   0.96293    0.07466  12.898  < 2e-16 ***
## category_code_LT01_5_count   0.91697    0.06246  14.680  < 2e-16 ***
## category_code_LT01_6_count   0.49483    0.15322   3.229  0.00132 ** 
## category_code_LT01_10_count  0.10593    0.11455   0.925  0.35553    
## category_code_LT01_15_count  0.16175    0.75621   0.214  0.83072    
## category_code_LT01_16_count  1.45322    1.17371   1.238  0.21625    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6223, Adjusted R-squared:  0.6177 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.626407517886675 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0121 -0.7475  0.0185  0.9615  3.7554 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99452    0.08672 115.246  < 2e-16 ***
## category_code_LT01_4_count   0.78087    0.09020   8.657  < 2e-16 ***
## category_code_LT01_5_count   0.91285    0.06195  14.736  < 2e-16 ***
## category_code_LT01_6_count   0.40787    0.15213   2.681 0.007585 ** 
## category_code_LT01_11_count  0.42125    0.11498   3.664 0.000276 ***
## category_code_LT01_12_count -0.08297    0.21184  -0.392 0.695465    
## category_code_LT01_13_count  0.09496    0.24223   0.392 0.695205    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6309, Adjusted R-squared:  0.6264 
## F-statistic: 139.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.626578672428374 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0119 -0.7414  0.0320  0.9252  3.7526 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99669    0.08676 115.227  < 2e-16 ***
## category_code_LT01_4_count   0.77396    0.09133   8.475 2.77e-16 ***
## category_code_LT01_5_count   0.90940    0.06226  14.606  < 2e-16 ***
## category_code_LT01_6_count   0.41599    0.15283   2.722 0.006720 ** 
## category_code_LT01_11_count  0.42216    0.11480   3.678 0.000262 ***
## category_code_LT01_12_count -0.09208    0.21244  -0.433 0.664883    
## category_code_LT01_14_count  0.20181    0.32790   0.615 0.538529    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6311, Adjusted R-squared:  0.6266 
## F-statistic:   140 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.626291394547044 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0128 -0.7368  0.0185  0.9595  3.7535 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99479    0.08673 115.234  < 2e-16 ***
## category_code_LT01_4_count   0.78435    0.09003   8.712  < 2e-16 ***
## category_code_LT01_5_count   0.91348    0.06195  14.746  < 2e-16 ***
## category_code_LT01_6_count   0.40633    0.15227   2.668 0.007874 ** 
## category_code_LT01_11_count  0.42355    0.11505   3.682 0.000258 ***
## category_code_LT01_12_count -0.08143    0.21198  -0.384 0.701049    
## category_code_LT01_15_count  0.02445    0.74691   0.033 0.973901    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6308, Adjusted R-squared:  0.6263 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.627225218785827 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0105 -0.7436  0.0322  0.9525  3.7586 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99420    0.08663 115.370  < 2e-16 ***
## category_code_LT01_4_count   0.78010    0.08969   8.698  < 2e-16 ***
## category_code_LT01_5_count   0.91097    0.06190  14.716  < 2e-16 ***
## category_code_LT01_6_count   0.41831    0.15229   2.747 0.006241 ** 
## category_code_LT01_11_count  0.41702    0.11483   3.632 0.000311 ***
## category_code_LT01_12_count -0.08067    0.21158  -0.381 0.703162    
## category_code_LT01_16_count  1.28483    1.15799   1.110 0.267744    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6317, Adjusted R-squared:  0.6272 
## F-statistic: 140.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.626550791898078 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0092 -0.7410  0.0368  0.9308  3.7641 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99577    0.08675 115.227  < 2e-16 ***
## category_code_LT01_4_count   0.77078    0.09182   8.394 5.05e-16 ***
## category_code_LT01_5_count   0.90687    0.06213  14.596  < 2e-16 ***
## category_code_LT01_6_count   0.41131    0.15225   2.701 0.007142 ** 
## category_code_LT01_11_count  0.40688    0.11130   3.656 0.000284 ***
## category_code_LT01_13_count  0.09416    0.24215   0.389 0.697557    
## category_code_LT01_14_count  0.19112    0.32688   0.585 0.559035    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6311, Adjusted R-squared:  0.6266 
## F-statistic:   140 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.626294722247791 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0104 -0.7436  0.0283  0.9623  3.7641 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99403    0.08673 115.235  < 2e-16 ***
## category_code_LT01_4_count   0.78030    0.09058   8.614  < 2e-16 ***
## category_code_LT01_5_count   0.91102    0.06178  14.747  < 2e-16 ***
## category_code_LT01_6_count   0.40249    0.15176   2.652 0.008258 ** 
## category_code_LT01_11_count  0.40932    0.11143   3.673 0.000266 ***
## category_code_LT01_13_count  0.09462    0.24275   0.390 0.696868    
## category_code_LT01_15_count  0.05378    0.74802   0.072 0.942719    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6308, Adjusted R-squared:  0.6263 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.627253984226748 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0079 -0.7519  0.0355  0.9547  3.7693 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99341    0.08662 115.374  < 2e-16 ***
## category_code_LT01_4_count   0.77592    0.09020   8.602  < 2e-16 ***
## category_code_LT01_5_count   0.90838    0.06173  14.716  < 2e-16 ***
## category_code_LT01_6_count   0.41508    0.15182   2.734 0.006482 ** 
## category_code_LT01_11_count  0.40278    0.11126   3.620 0.000325 ***
## category_code_LT01_13_count  0.10364    0.24209   0.428 0.668761    
## category_code_LT01_16_count  1.30520    1.15874   1.126 0.260548    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6318, Adjusted R-squared:  0.6273 
## F-statistic: 140.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.626436914912337 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0100 -0.7472  0.0216  0.9277  3.7621 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99603    0.08676 115.215  < 2e-16 ***
## category_code_LT01_4_count   0.77422    0.09163   8.450 3.34e-16 ***
## category_code_LT01_5_count   0.90756    0.06214  14.606  < 2e-16 ***
## category_code_LT01_6_count   0.40980    0.15239   2.689  0.00741 ** 
## category_code_LT01_11_count  0.40936    0.11127   3.679  0.00026 ***
## category_code_LT01_14_count  0.19033    0.32696   0.582  0.56074    
## category_code_LT01_15_count  0.02871    0.74636   0.038  0.96933    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6309, Adjusted R-squared:  0.6264 
## F-statistic: 139.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.62743241159668 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0075 -0.7581  0.0350  0.9111  3.7673 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99562    0.08664 115.364  < 2e-16 ***
## category_code_LT01_4_count   0.76874    0.09135   8.415 4.32e-16 ***
## category_code_LT01_5_count   0.90453    0.06209  14.568  < 2e-16 ***
## category_code_LT01_6_count   0.42319    0.15247   2.776 0.005721 ** 
## category_code_LT01_11_count  0.40241    0.11113   3.621 0.000324 ***
## category_code_LT01_14_count  0.21155    0.32700   0.647 0.517984    
## category_code_LT01_16_count  1.32883    1.15949   1.146 0.252333    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6319, Adjusted R-squared:  0.6274 
## F-statistic: 140.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.627119280113921 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0088 -0.7399  0.0356  0.9535  3.7672 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99372    0.08663 115.360  < 2e-16 ***
## category_code_LT01_4_count   0.77946    0.09003   8.658  < 2e-16 ***
## category_code_LT01_5_count   0.90919    0.06173  14.729  < 2e-16 ***
## category_code_LT01_6_count   0.41308    0.15193   2.719 0.006783 ** 
## category_code_LT01_11_count  0.40535    0.11123   3.644 0.000297 ***
## category_code_LT01_15_count  0.05697    0.74587   0.076 0.939148    
## category_code_LT01_16_count  1.28909    1.15856   1.113 0.266397    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.375 on 491 degrees of freedom
## Multiple R-squared:  0.6316, Adjusted R-squared:  0.6271 
## F-statistic: 140.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616570317372917 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0078 -0.7810  0.0053  0.8999  4.0504 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99144    0.08790 113.665  < 2e-16 ***
## category_code_LT01_4_count   0.95321    0.07794  12.230  < 2e-16 ***
## category_code_LT01_5_count   0.91103    0.06311  14.436  < 2e-16 ***
## category_code_LT01_6_count   0.50961    0.15277   3.336 0.000915 ***
## category_code_LT01_12_count  0.10131    0.20839   0.486 0.627078    
## category_code_LT01_13_count  0.14597    0.24500   0.596 0.551601    
## category_code_LT01_14_count  0.23062    0.33218   0.694 0.487842    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6166 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616265800285632 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0091 -0.7814  0.0106  0.9180  4.0526 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98930    0.08788 113.669  < 2e-16 ***
## category_code_LT01_4_count   0.96267    0.07659  12.569  < 2e-16 ***
## category_code_LT01_5_count   0.91597    0.06279  14.589  < 2e-16 ***
## category_code_LT01_6_count   0.49662    0.15234   3.260  0.00119 ** 
## category_code_LT01_12_count  0.11524    0.20769   0.555  0.57923    
## category_code_LT01_13_count  0.14969    0.24555   0.610  0.54240    
## category_code_LT01_15_count  0.22950    0.75670   0.303  0.76179    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6209, Adjusted R-squared:  0.6163 
## F-statistic:   134 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617528338772129 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0061 -0.7782  0.0167  0.9486  4.0533 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98863    0.08774 113.847  < 2e-16 ***
## category_code_LT01_4_count   0.95670    0.07590  12.604  < 2e-16 ***
## category_code_LT01_5_count   0.91258    0.06272  14.550  < 2e-16 ***
## category_code_LT01_6_count   0.51159    0.15214   3.363 0.000832 ***
## category_code_LT01_12_count  0.11120    0.20733   0.536 0.591959    
## category_code_LT01_13_count  0.15608    0.24484   0.637 0.524108    
## category_code_LT01_16_count  1.53394    1.17198   1.309 0.191198    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6175 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616343597745127 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0091 -0.7814  0.0000  0.9038  4.0501 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99182    0.08793 113.638  < 2e-16 ***
## category_code_LT01_4_count   0.95803    0.07767  12.335  < 2e-16 ***
## category_code_LT01_5_count   0.91231    0.06312  14.454  < 2e-16 ***
## category_code_LT01_6_count   0.50612    0.15306   3.307  0.00101 ** 
## category_code_LT01_12_count  0.10634    0.20840   0.510  0.61008    
## category_code_LT01_14_count  0.22814    0.33233   0.686  0.49273    
## category_code_LT01_15_count  0.19196    0.75534   0.254  0.79950    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6163 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.61766627505538 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0060 -0.7810 -0.0085  0.9158  4.0505 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99141    0.08778 113.829  < 2e-16 ***
## category_code_LT01_4_count   0.95025    0.07721  12.308  < 2e-16 ***
## category_code_LT01_5_count   0.90846    0.06305  14.408  < 2e-16 ***
## category_code_LT01_6_count   0.52194    0.15288   3.414 0.000693 ***
## category_code_LT01_12_count  0.10122    0.20802   0.487 0.626774    
## category_code_LT01_14_count  0.25380    0.33220   0.764 0.445245    
## category_code_LT01_16_count  1.55746    1.17284   1.328 0.184817    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6223, Adjusted R-squared:  0.6177 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617280667268458 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0075 -0.7838 -0.0015  0.9611  4.0528 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98907    0.08776 113.818  < 2e-16 ***
## category_code_LT01_4_count   0.96153    0.07567  12.707  < 2e-16 ***
## category_code_LT01_5_count   0.91396    0.06273  14.571  < 2e-16 ***
## category_code_LT01_6_count   0.50762    0.15240   3.331 0.000931 ***
## category_code_LT01_12_count  0.11657    0.20734   0.562 0.574215    
## category_code_LT01_15_count  0.22430    0.75450   0.297 0.766378    
## category_code_LT01_16_count  1.51665    1.17200   1.294 0.196250    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616447557664737 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0103 -0.7780  0.0240  0.8888  4.0498 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99208    0.08791 113.665  < 2e-16 ***
## category_code_LT01_4_count   0.95574    0.07788  12.271  < 2e-16 ***
## category_code_LT01_5_count   0.91366    0.06295  14.513  < 2e-16 ***
## category_code_LT01_6_count   0.51747    0.15157   3.414 0.000693 ***
## category_code_LT01_13_count  0.15394    0.24539   0.627 0.530736    
## category_code_LT01_14_count  0.24338    0.33098   0.735 0.462492    
## category_code_LT01_15_count  0.21278    0.75649   0.281 0.778617    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6211, Adjusted R-squared:  0.6164 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617818884858799 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0069 -0.7811  0.0100  0.8989  4.0503 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99160    0.08775 113.862  < 2e-16 ***
## category_code_LT01_4_count   0.94735    0.07740  12.239  < 2e-16 ***
## category_code_LT01_5_count   0.90953    0.06289  14.462  < 2e-16 ***
## category_code_LT01_6_count   0.53334    0.15139   3.523 0.000467 ***
## category_code_LT01_13_count  0.16095    0.24463   0.658 0.510870    
## category_code_LT01_14_count  0.26900    0.33082   0.813 0.416543    
## category_code_LT01_16_count  1.59186    1.17316   1.357 0.175435    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6224, Adjusted R-squared:  0.6178 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617387902115378 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0088 -0.7787  0.0073  0.9285  4.0527 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98919    0.08775 113.839  < 2e-16 ***
## category_code_LT01_4_count   0.96000    0.07565  12.690  < 2e-16 ***
## category_code_LT01_5_count   0.91576    0.06252  14.649  < 2e-16 ***
## category_code_LT01_6_count   0.51964    0.15107   3.440 0.000632 ***
## category_code_LT01_13_count  0.16520    0.24524   0.674 0.500850    
## category_code_LT01_15_count  0.24760    0.75572   0.328 0.743326    
## category_code_LT01_16_count  1.55055    1.17252   1.322 0.186648    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_6_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617540401509149 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0085 -0.7816  0.0231  0.9045  4.0498 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.99206    0.08778 113.829  < 2e-16 ***
## category_code_LT01_4_count   0.95318    0.07701  12.377  < 2e-16 ***
## category_code_LT01_5_count   0.91110    0.06290  14.485  < 2e-16 ***
## category_code_LT01_6_count   0.52995    0.15166   3.494 0.000518 ***
## category_code_LT01_14_count  0.26679    0.33098   0.806 0.420587    
## category_code_LT01_15_count  0.20666    0.75418   0.274 0.784187    
## category_code_LT01_16_count  1.57301    1.17322   1.341 0.180616    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6175 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count 0.620299729747341 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0066 -0.7686 -0.0138  0.8642  3.9310 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97904    0.09069 110.040   <2e-16 ***
## category_code_LT01_4_count   0.94684    0.07423  12.756   <2e-16 ***
## category_code_LT01_5_count   0.92713    0.06275  14.775   <2e-16 ***
## category_code_LT01_7_count   0.48218    0.15517   3.107   0.0020 ** 
## category_code_LT01_8_count  -0.18115    0.27497  -0.659   0.5103    
## category_code_LT01_9_count   0.43997    0.22720   1.937   0.0534 .  
## category_code_LT01_10_count  0.11999    0.11324   1.060   0.2898    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6249, Adjusted R-squared:  0.6203 
## F-statistic: 136.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count 0.62801977918778 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0274 -0.7477  0.0283  0.9025  3.7726 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00572    0.08638 115.828  < 2e-16 ***
## category_code_LT01_4_count   0.78581    0.08883   8.846  < 2e-16 ***
## category_code_LT01_5_count   0.91873    0.06216  14.779  < 2e-16 ***
## category_code_LT01_7_count   0.36068    0.15822   2.280  0.02306 *  
## category_code_LT01_8_count  -0.14731    0.27226  -0.541  0.58872    
## category_code_LT01_9_count   0.41017    0.22390   1.832  0.06757 .  
## category_code_LT01_11_count  0.38023    0.11293   3.367  0.00082 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6325, Adjusted R-squared:  0.628 
## F-statistic: 140.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count 0.620089807679342 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0276 -0.7865 -0.0086  0.8891  4.0382 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00365    0.08732 114.570  < 2e-16 ***
## category_code_LT01_4_count   0.94095    0.07564  12.440  < 2e-16 ***
## category_code_LT01_5_count   0.92204    0.06303  14.628  < 2e-16 ***
## category_code_LT01_7_count   0.49222    0.15480   3.180  0.00157 ** 
## category_code_LT01_8_count  -0.18530    0.27519  -0.673  0.50102    
## category_code_LT01_9_count   0.46476    0.22563   2.060  0.03994 *  
## category_code_LT01_12_count  0.18909    0.20499   0.922  0.35675    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6247, Adjusted R-squared:  0.6201 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count 0.619493556456134 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0321 -0.7937 -0.0210  0.8467  4.0370 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00489    0.08737 114.507  < 2e-16 ***
## category_code_LT01_4_count   0.95413    0.07433  12.836  < 2e-16 ***
## category_code_LT01_5_count   0.92674    0.06285  14.744  < 2e-16 ***
## category_code_LT01_7_count   0.48861    0.15621   3.128  0.00186 ** 
## category_code_LT01_8_count  -0.17155    0.27572  -0.622  0.53410    
## category_code_LT01_9_count   0.47364    0.22630   2.093  0.03686 *  
## category_code_LT01_13_count  0.06987    0.24676   0.283  0.77717    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6241, Adjusted R-squared:  0.6195 
## F-statistic: 135.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count 0.619436866963043 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0328 -0.7950 -0.0280  0.8747  4.0364 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00548    0.08746 114.398  < 2e-16 ***
## category_code_LT01_4_count   0.95574    0.07493  12.755  < 2e-16 ***
## category_code_LT01_5_count   0.92686    0.06309  14.691  < 2e-16 ***
## category_code_LT01_7_count   0.49348    0.15523   3.179  0.00157 ** 
## category_code_LT01_8_count  -0.17648    0.27526  -0.641  0.52173    
## category_code_LT01_9_count   0.46804    0.22620   2.069  0.03906 *  
## category_code_LT01_14_count  0.02765    0.32986   0.084  0.93322    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.624,  Adjusted R-squared:  0.6194 
## F-statistic: 135.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count 0.619675195326572 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0330 -0.7913 -0.0221  0.8659  4.0368 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00506    0.08735 114.543  < 2e-16 ***
## category_code_LT01_4_count   0.94924    0.07493  12.669  < 2e-16 ***
## category_code_LT01_5_count   0.92777    0.06281  14.772  < 2e-16 ***
## category_code_LT01_7_count   0.49636    0.15492   3.204  0.00144 ** 
## category_code_LT01_8_count  -0.17818    0.27518  -0.648  0.51760    
## category_code_LT01_9_count   0.47082    0.22572   2.086  0.03751 *  
## category_code_LT01_15_count  0.42131    0.75100   0.561  0.57506    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6243, Adjusted R-squared:  0.6197 
## F-statistic:   136 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_16_count 0.620225284064489 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0322 -0.7928  0.0105  0.8649  4.0365 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00538    0.08728 114.629  < 2e-16 ***
## category_code_LT01_4_count   0.95278    0.07374  12.921  < 2e-16 ***
## category_code_LT01_5_count   0.92612    0.06277  14.754  < 2e-16 ***
## category_code_LT01_7_count   0.49477    0.15476   3.197  0.00148 ** 
## category_code_LT01_8_count  -0.18982    0.27529  -0.690  0.49082    
## category_code_LT01_9_count   0.45880    0.22577   2.032  0.04268 *  
## category_code_LT01_16_count  1.18291    1.16762   1.013  0.31151    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6248, Adjusted R-squared:  0.6202 
## F-statistic: 136.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count 0.626465569559947 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0104 -0.7697  0.0399  0.8966  3.6481 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98372    0.08995 110.988  < 2e-16 ***
## category_code_LT01_4_count   0.79403    0.08888   8.934  < 2e-16 ***
## category_code_LT01_5_count   0.92588    0.06215  14.898  < 2e-16 ***
## category_code_LT01_7_count   0.37271    0.15837   2.353 0.018996 *  
## category_code_LT01_8_count  -0.13770    0.27275  -0.505 0.613874    
## category_code_LT01_10_count  0.12723    0.11163   1.140 0.254951    
## category_code_LT01_11_count  0.38995    0.11296   3.452 0.000604 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.631,  Adjusted R-squared:  0.6265 
## F-statistic: 139.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count 0.618030660011758 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0092 -0.7689  0.0147  0.8672  3.9070 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97934    0.09096 109.715  < 2e-16 ***
## category_code_LT01_4_count   0.95590    0.07532  12.691  < 2e-16 ***
## category_code_LT01_5_count   0.93056    0.06305  14.759  < 2e-16 ***
## category_code_LT01_7_count   0.51021    0.15488   3.294  0.00106 ** 
## category_code_LT01_8_count  -0.17488    0.27586  -0.634  0.52640    
## category_code_LT01_10_count  0.14157    0.11288   1.254  0.21037    
## category_code_LT01_12_count  0.18530    0.20575   0.901  0.36824    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6226, Adjusted R-squared:  0.618 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count 0.61740890003356 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0132 -0.7693  0.0239  0.8485  3.9014 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97975    0.09103 109.632  < 2e-16 ***
## category_code_LT01_4_count   0.97036    0.07391  13.129  < 2e-16 ***
## category_code_LT01_5_count   0.93562    0.06286  14.885  < 2e-16 ***
## category_code_LT01_7_count   0.50995    0.15610   3.267  0.00116 ** 
## category_code_LT01_8_count  -0.16421    0.27645  -0.594  0.55279    
## category_code_LT01_10_count  0.14634    0.11286   1.297  0.19536    
## category_code_LT01_13_count  0.02685    0.24691   0.109  0.91346    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count 0.617402792177685 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0130 -0.7687  0.0208  0.8552  3.8999 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97918    0.09149 109.077  < 2e-16 ***
## category_code_LT01_4_count   0.97206    0.07445  13.057  < 2e-16 ***
## category_code_LT01_5_count   0.93620    0.06312  14.832  < 2e-16 ***
## category_code_LT01_7_count   0.51249    0.15521   3.302  0.00103 ** 
## category_code_LT01_8_count  -0.16594    0.27592  -0.601  0.54785    
## category_code_LT01_10_count  0.14814    0.11539   1.284  0.19982    
## category_code_LT01_14_count -0.02131    0.33762  -0.063  0.94970    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.622,  Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count 0.617538745459179 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0144 -0.7702  0.0199  0.8452  3.9047 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98062    0.09104 109.633  < 2e-16 ***
## category_code_LT01_4_count   0.96598    0.07448  12.970  < 2e-16 ***
## category_code_LT01_5_count   0.93619    0.06282  14.902  < 2e-16 ***
## category_code_LT01_7_count   0.51412    0.15505   3.316 0.000981 ***
## category_code_LT01_8_count  -0.16731    0.27588  -0.606 0.544482    
## category_code_LT01_10_count  0.14249    0.11323   1.258 0.208832    
## category_code_LT01_15_count  0.31936    0.75586   0.423 0.672833    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6222, Adjusted R-squared:  0.6175 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_16_count 0.618241575647847 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0137 -0.7707  0.0252  0.8616  3.9061 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98113    0.09094 109.755   <2e-16 ***
## category_code_LT01_4_count   0.96699    0.07346  13.163   <2e-16 ***
## category_code_LT01_5_count   0.93438    0.06278  14.884   <2e-16 ***
## category_code_LT01_7_count   0.51234    0.15482   3.309    0.001 ** 
## category_code_LT01_8_count  -0.18018    0.27594  -0.653    0.514    
## category_code_LT01_10_count  0.14080    0.11285   1.248    0.213    
## category_code_LT01_16_count  1.21840    1.17089   1.041    0.299    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6229, Adjusted R-squared:  0.6182 
## F-statistic: 135.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count 0.625477375162192 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0390 -0.7457  0.0346  0.9256  3.7551 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.011873   0.086631 115.569  < 2e-16 ***
## category_code_LT01_4_count   0.803624   0.088652   9.065  < 2e-16 ***
## category_code_LT01_5_count   0.926611   0.062444  14.839  < 2e-16 ***
## category_code_LT01_7_count   0.385464   0.158447   2.433 0.015340 *  
## category_code_LT01_8_count  -0.130795   0.273334  -0.479 0.632494    
## category_code_LT01_11_count  0.396666   0.117653   3.371 0.000807 ***
## category_code_LT01_12_count -0.001505   0.211924  -0.007 0.994337    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6255 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count 0.625478574776581 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0389 -0.7455  0.0347  0.9261  3.7554 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.011834   0.086616 115.589  < 2e-16 ***
## category_code_LT01_4_count   0.803314   0.088890   9.037  < 2e-16 ***
## category_code_LT01_5_count   0.926504   0.062251  14.883  < 2e-16 ***
## category_code_LT01_7_count   0.384822   0.159149   2.418 0.015969 *  
## category_code_LT01_8_count  -0.130211   0.273552  -0.476 0.634284    
## category_code_LT01_11_count  0.396304   0.113013   3.507 0.000495 ***
## category_code_LT01_13_count  0.009843   0.244325   0.040 0.967880    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6255 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count 0.625501713037439 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0389 -0.7394  0.0344  0.9122  3.7547 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01252    0.08669 115.500  < 2e-16 ***
## category_code_LT01_4_count   0.80115    0.08965   8.936  < 2e-16 ***
## category_code_LT01_5_count   0.92550    0.06251  14.805  < 2e-16 ***
## category_code_LT01_7_count   0.38369    0.15851   2.421 0.015857 *  
## category_code_LT01_8_count  -0.13151    0.27305  -0.482 0.630293    
## category_code_LT01_11_count  0.39624    0.11297   3.507 0.000494 ***
## category_code_LT01_14_count  0.05839    0.32662   0.179 0.858190    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:   0.63,  Adjusted R-squared:  0.6255 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count 0.625534269146152 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0392 -0.7404  0.0337  0.9162  3.7569 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01183    0.08661 115.601  < 2e-16 ***
## category_code_LT01_4_count   0.80103    0.08909   8.991  < 2e-16 ***
## category_code_LT01_5_count   0.92686    0.06223  14.894  < 2e-16 ***
## category_code_LT01_7_count   0.38744    0.15832   2.447 0.014747 *  
## category_code_LT01_8_count  -0.13197    0.27305  -0.483 0.629096    
## category_code_LT01_11_count  0.39409    0.11329   3.479 0.000549 ***
## category_code_LT01_15_count  0.20417    0.74728   0.273 0.784798    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.378 on 491 degrees of freedom
## Multiple R-squared:  0.6301, Adjusted R-squared:  0.6255 
## F-statistic: 139.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_16_count 0.626185903267659 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0382 -0.7351  0.0402  0.9149  3.7584 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01194    0.08653 115.703  < 2e-16 ***
## category_code_LT01_4_count   0.80130    0.08855   9.049  < 2e-16 ***
## category_code_LT01_5_count   0.92534    0.06218  14.881  < 2e-16 ***
## category_code_LT01_7_count   0.38694    0.15803   2.448 0.014695 *  
## category_code_LT01_8_count  -0.14441    0.27314  -0.529 0.597250    
## category_code_LT01_11_count  0.39173    0.11297   3.468 0.000571 ***
## category_code_LT01_16_count  1.11744    1.15830   0.965 0.335158    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6307, Adjusted R-squared:  0.6262 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count 0.616816260406163 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0407 -0.7877  0.0083  0.8573  4.0314 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01049    0.08763 114.238  < 2e-16 ***
## category_code_LT01_4_count   0.96787    0.07519  12.872  < 2e-16 ***
## category_code_LT01_5_count   0.93097    0.06317  14.738  < 2e-16 ***
## category_code_LT01_7_count   0.52487    0.15569   3.371 0.000807 ***
## category_code_LT01_8_count  -0.16652    0.27680  -0.602 0.547718    
## category_code_LT01_12_count  0.19744    0.20592   0.959 0.338126    
## category_code_LT01_13_count  0.02701    0.24715   0.109 0.913018    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6168 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count 0.616822069159869 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0408 -0.7880  0.0099  0.8639  4.0308 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01109    0.08771 114.139  < 2e-16 ***
## category_code_LT01_4_count   0.96694    0.07588  12.743  < 2e-16 ***
## category_code_LT01_5_count   0.93036    0.06340  14.674  < 2e-16 ***
## category_code_LT01_7_count   0.52545    0.15491   3.392  0.00075 ***
## category_code_LT01_8_count  -0.16880    0.27626  -0.611  0.54146    
## category_code_LT01_12_count  0.19597    0.20640   0.949  0.34284    
## category_code_LT01_14_count  0.04613    0.33129   0.139  0.88932    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6168 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count 0.617038531719492 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0411 -0.7934  0.0072  0.8635  4.0314 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01048    0.08760 114.274  < 2e-16 ***
## category_code_LT01_4_count   0.96130    0.07596  12.655  < 2e-16 ***
## category_code_LT01_5_count   0.93155    0.06313  14.755  < 2e-16 ***
## category_code_LT01_7_count   0.52904    0.15455   3.423 0.000671 ***
## category_code_LT01_8_count  -0.17034    0.27619  -0.617 0.537689    
## category_code_LT01_12_count  0.19954    0.20578   0.970 0.332688    
## category_code_LT01_15_count  0.41064    0.75360   0.545 0.586062    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.617 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_16_count 0.617754688257407 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0398 -0.7936  0.0115  0.8641  4.0312 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01064    0.08752 114.383  < 2e-16 ***
## category_code_LT01_4_count   0.96360    0.07480  12.883  < 2e-16 ***
## category_code_LT01_5_count   0.92958    0.06309  14.735  < 2e-16 ***
## category_code_LT01_7_count   0.52659    0.15436   3.412 0.000699 ***
## category_code_LT01_8_count  -0.18368    0.27625  -0.665 0.506436    
## category_code_LT01_12_count  0.19817    0.20557   0.964 0.335515    
## category_code_LT01_16_count  1.29115    1.17020   1.103 0.270412    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6224, Adjusted R-squared:  0.6178 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616133801044834 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0460 -0.7856  0.0132  0.8291  4.0290 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01288    0.08777 114.083  < 2e-16 ***
## category_code_LT01_4_count   0.98147    0.07464  13.150  < 2e-16 ***
## category_code_LT01_5_count   0.93526    0.06325  14.786  < 2e-16 ***
## category_code_LT01_7_count   0.52451    0.15621   3.358 0.000847 ***
## category_code_LT01_8_count  -0.15708    0.27686  -0.567 0.570717    
## category_code_LT01_13_count  0.03458    0.24727   0.140 0.888845    
## category_code_LT01_14_count  0.06996    0.33068   0.212 0.832543    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6208, Adjusted R-squared:  0.6161 
## F-statistic:   134 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count 0.616327613611308 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0463 -0.7578  0.0056  0.8328  4.0299 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01201    0.08767 114.204  < 2e-16 ***
## category_code_LT01_4_count   0.97694    0.07453  13.108  < 2e-16 ***
## category_code_LT01_5_count   0.93694    0.06294  14.885  < 2e-16 ***
## category_code_LT01_7_count   0.52836    0.15580   3.391 0.000752 ***
## category_code_LT01_8_count  -0.15767    0.27678  -0.570 0.569159    
## category_code_LT01_13_count  0.04197    0.24762   0.170 0.865469    
## category_code_LT01_15_count  0.40883    0.75554   0.541 0.588673    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6163 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_16_count 0.61705432789913 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0451 -0.7621  0.0193  0.8365  4.0297 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01216    0.08758 114.314  < 2e-16 ***
## category_code_LT01_4_count   0.97905    0.07330  13.357  < 2e-16 ***
## category_code_LT01_5_count   0.93492    0.06290  14.864  < 2e-16 ***
## category_code_LT01_7_count   0.52586    0.15563   3.379 0.000786 ***
## category_code_LT01_8_count  -0.17112    0.27683  -0.618 0.536768    
## category_code_LT01_13_count  0.04254    0.24708   0.172 0.863382    
## category_code_LT01_16_count  1.29704    1.17183   1.107 0.268898    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616337478202894 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0465 -0.7726 -0.0033  0.8398  4.0290 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01288    0.08774 114.117  < 2e-16 ***
## category_code_LT01_4_count   0.97567    0.07527  12.962  < 2e-16 ***
## category_code_LT01_5_count   0.93600    0.06321  14.807  < 2e-16 ***
## category_code_LT01_7_count   0.52932    0.15505   3.414 0.000694 ***
## category_code_LT01_8_count  -0.16124    0.27628  -0.584 0.559736    
## category_code_LT01_14_count  0.06723    0.33061   0.203 0.838935    
## category_code_LT01_15_count  0.39929    0.75429   0.529 0.596793    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.621,  Adjusted R-squared:  0.6163 
## F-statistic: 134.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617085961348876 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0453 -0.7827  0.0078  0.8577  4.0286 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01326    0.08766 114.232  < 2e-16 ***
## category_code_LT01_4_count   0.97671    0.07421  13.161  < 2e-16 ***
## category_code_LT01_5_count   0.93361    0.06317  14.780  < 2e-16 ***
## category_code_LT01_7_count   0.52624    0.15485   3.398 0.000733 ***
## category_code_LT01_8_count  -0.17509    0.27634  -0.634 0.526640    
## category_code_LT01_14_count  0.08761    0.33065   0.265 0.791150    
## category_code_LT01_16_count  1.30607    1.17263   1.114 0.265913    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6217, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_8_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617278471201992 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0457 -0.7576 -0.0022  0.8577  4.0297 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01221    0.08756 114.351  < 2e-16 ***
## category_code_LT01_4_count   0.97292    0.07400  13.148  < 2e-16 ***
## category_code_LT01_5_count   0.93568    0.06286  14.886  < 2e-16 ***
## category_code_LT01_7_count   0.53132    0.15448   3.439 0.000633 ***
## category_code_LT01_8_count  -0.17611    0.27627  -0.637 0.524115    
## category_code_LT01_15_count  0.42443    0.75358   0.563 0.573544    
## category_code_LT01_16_count  1.30893    1.17137   1.117 0.264352    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.628442757311434 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9998 -0.7668  0.0226  0.9217  3.6845 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98175    0.08969 111.292  < 2e-16 ***
## category_code_LT01_4_count   0.77795    0.08906   8.735  < 2e-16 ***
## category_code_LT01_5_count   0.91351    0.06145  14.867  < 2e-16 ***
## category_code_LT01_7_count   0.34859    0.15834   2.202 0.028157 *  
## category_code_LT01_9_count   0.38152    0.22524   1.694 0.090933 .  
## category_code_LT01_10_count  0.10347    0.11210   0.923 0.356435    
## category_code_LT01_11_count  0.37792    0.11290   3.347 0.000879 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 491 degrees of freedom
## Multiple R-squared:  0.6329, Adjusted R-squared:  0.6284 
## F-statistic: 141.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 0.620522686296484 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9969 -0.7667 -0.0007  0.8976  3.9394 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97713    0.09063 110.082  < 2e-16 ***
## category_code_LT01_4_count   0.93233    0.07609  12.253  < 2e-16 ***
## category_code_LT01_5_count   0.91591    0.06235  14.689  < 2e-16 ***
## category_code_LT01_7_count   0.47781    0.15508   3.081  0.00218 ** 
## category_code_LT01_9_count   0.43256    0.22707   1.905  0.05737 .  
## category_code_LT01_10_count  0.11411    0.11332   1.007  0.31443    
## category_code_LT01_12_count  0.17426    0.20498   0.850  0.39566    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6251, Adjusted R-squared:  0.6205 
## F-statistic: 136.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 0.620029021898737 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0006 -0.7671 -0.0126  0.8695  3.9349 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97758    0.09069 110.017  < 2e-16 ***
## category_code_LT01_4_count   0.94393    0.07484  12.613  < 2e-16 ***
## category_code_LT01_5_count   0.92062    0.06212  14.821  < 2e-16 ***
## category_code_LT01_7_count   0.47376    0.15638   3.030  0.00258 ** 
## category_code_LT01_9_count   0.44063    0.22781   1.934  0.05367 .  
## category_code_LT01_10_count  0.11774    0.11332   1.039  0.29930    
## category_code_LT01_13_count  0.07132    0.24626   0.290  0.77224    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:   0.62 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 0.619979258358923 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0002 -0.7659 -0.0091  0.8741  3.9315 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97631    0.09115 109.446   <2e-16 ***
## category_code_LT01_4_count   0.94829    0.07519  12.612   <2e-16 ***
## category_code_LT01_5_count   0.92191    0.06238  14.778   <2e-16 ***
## category_code_LT01_7_count   0.48045    0.15536   3.092   0.0021 ** 
## category_code_LT01_9_count   0.43692    0.22736   1.922   0.0552 .  
## category_code_LT01_10_count  0.12204    0.11571   1.055   0.2921    
## category_code_LT01_14_count -0.04710    0.33670  -0.140   0.8888    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:   0.62 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 0.62012935892787 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0020 -0.7673 -0.0135  0.8734  3.9380 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97851    0.09070 110.015  < 2e-16 ***
## category_code_LT01_4_count   0.94072    0.07534  12.486  < 2e-16 ***
## category_code_LT01_5_count   0.92139    0.06209  14.839  < 2e-16 ***
## category_code_LT01_7_count   0.48154    0.15521   3.102  0.00203 ** 
## category_code_LT01_9_count   0.43817    0.22722   1.928  0.05438 .  
## category_code_LT01_10_count  0.11408    0.11370   1.003  0.31616    
## category_code_LT01_15_count  0.34821    0.75345   0.462  0.64417    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6247, Adjusted R-squared:  0.6201 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 0.620639220916267 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0010 -0.7670 -0.0099  0.8810  3.9380 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97872    0.09063 110.108  < 2e-16 ***
## category_code_LT01_4_count   0.94325    0.07428  12.698  < 2e-16 ***
## category_code_LT01_5_count   0.91954    0.06207  14.815  < 2e-16 ***
## category_code_LT01_7_count   0.48011    0.15504   3.097  0.00207 ** 
## category_code_LT01_9_count   0.42700    0.22720   1.879  0.06078 .  
## category_code_LT01_10_count  0.11395    0.11329   1.006  0.31499    
## category_code_LT01_16_count  1.09067    1.16679   0.935  0.35037    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6252, Adjusted R-squared:  0.6206 
## F-statistic: 136.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.627798738592179 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0227 -0.7420  0.0309  0.9091  3.7719 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.004368   0.086390 115.804  < 2e-16 ***
## category_code_LT01_4_count   0.784795   0.088889   8.829  < 2e-16 ***
## category_code_LT01_5_count   0.913934   0.061755  14.799  < 2e-16 ***
## category_code_LT01_7_count   0.357351   0.158421   2.256  0.02453 *  
## category_code_LT01_9_count   0.406185   0.223845   1.815  0.07020 .  
## category_code_LT01_11_count  0.383175   0.117513   3.261  0.00119 ** 
## category_code_LT01_12_count -0.006576   0.211039  -0.031  0.97515    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6323, Adjusted R-squared:  0.6278 
## F-statistic: 140.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.627829473707806 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0222 -0.7358  0.0313  0.9143  3.7734 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00416    0.08637 115.828  < 2e-16 ***
## category_code_LT01_4_count   0.78312    0.08917   8.783  < 2e-16 ***
## category_code_LT01_5_count   0.91345    0.06152  14.849  < 2e-16 ***
## category_code_LT01_7_count   0.35393    0.15920   2.223 0.026661 *  
## category_code_LT01_9_count   0.40954    0.22444   1.825 0.068654 .  
## category_code_LT01_11_count  0.38134    0.11298   3.375 0.000796 ***
## category_code_LT01_13_count  0.04967    0.24376   0.204 0.838623    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6323, Adjusted R-squared:  0.6278 
## F-statistic: 140.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.627800942603021 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0225 -0.7388  0.0309  0.9121  3.7725 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00455    0.08646 115.719  < 2e-16 ***
## category_code_LT01_4_count   0.78388    0.08980   8.730  < 2e-16 ***
## category_code_LT01_5_count   0.91340    0.06177  14.786  < 2e-16 ***
## category_code_LT01_7_count   0.35704    0.15846   2.253  0.02469 *  
## category_code_LT01_9_count   0.40532    0.22426   1.807  0.07132 .  
## category_code_LT01_11_count  0.38213    0.11291   3.384  0.00077 ***
## category_code_LT01_14_count  0.02032    0.32620   0.062  0.95037    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6323, Adjusted R-squared:  0.6278 
## F-statistic: 140.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.627866388810371 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0227 -0.7454  0.0233  0.9128  3.7745 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00425    0.08636 115.839  < 2e-16 ***
## category_code_LT01_4_count   0.78181    0.08934   8.751  < 2e-16 ***
## category_code_LT01_5_count   0.91400    0.06150  14.862  < 2e-16 ***
## category_code_LT01_7_count   0.35962    0.15829   2.272 0.023527 *  
## category_code_LT01_9_count   0.40741    0.22386   1.820 0.069381 .  
## category_code_LT01_11_count  0.37955    0.11323   3.352 0.000864 ***
## category_code_LT01_15_count  0.22379    0.74500   0.300 0.764012    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.374 on 491 degrees of freedom
## Multiple R-squared:  0.6324, Adjusted R-squared:  0.6279 
## F-statistic: 140.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.628361343392394 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0217 -0.7300  0.0314  0.9113  3.7752 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00439    0.08631 115.918  < 2e-16 ***
## category_code_LT01_4_count   0.78291    0.08879   8.818  < 2e-16 ***
## category_code_LT01_5_count   0.91242    0.06147  14.843  < 2e-16 ***
## category_code_LT01_7_count   0.35914    0.15806   2.272 0.023506 *  
## category_code_LT01_9_count   0.39770    0.22389   1.776 0.076300 .  
## category_code_LT01_11_count  0.37844    0.11291   3.352 0.000865 ***
## category_code_LT01_16_count  0.99601    1.15451   0.863 0.388717    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.373 on 491 degrees of freedom
## Multiple R-squared:  0.6328, Adjusted R-squared:  0.6284 
## F-statistic: 141.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 0.619806337235978 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0212 -0.7770 -0.0225  0.8722  4.0402 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00171    0.08731 114.551  < 2e-16 ***
## category_code_LT01_4_count   0.93835    0.07622  12.312  < 2e-16 ***
## category_code_LT01_5_count   0.91557    0.06243  14.666  < 2e-16 ***
## category_code_LT01_7_count   0.48348    0.15605   3.098  0.00206 ** 
## category_code_LT01_9_count   0.46501    0.22620   2.056  0.04033 *  
## category_code_LT01_12_count  0.18239    0.20502   0.890  0.37411    
## category_code_LT01_13_count  0.07266    0.24632   0.295  0.76814    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6244, Adjusted R-squared:  0.6198 
## F-statistic:   136 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 0.61973905518008 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0217 -0.7783 -0.0266  0.8923  4.0399 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.001962   0.087410 114.426  < 2e-16 ***
## category_code_LT01_4_count   0.940915   0.076658  12.274  < 2e-16 ***
## category_code_LT01_5_count   0.915925   0.062656  14.618  < 2e-16 ***
## category_code_LT01_7_count   0.489190   0.155117   3.154  0.00171 ** 
## category_code_LT01_9_count   0.460083   0.226045   2.035  0.04235 *  
## category_code_LT01_12_count  0.183996   0.205512   0.895  0.37106    
## category_code_LT01_14_count  0.003623   0.330608   0.011  0.99126    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6243, Adjusted R-squared:  0.6197 
## F-statistic:   136 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 0.619985109990246 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0218 -0.7740 -0.0256  0.8793  4.0401 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00180    0.08729 114.582   <2e-16 ***
## category_code_LT01_4_count   0.93326    0.07690  12.136   <2e-16 ***
## category_code_LT01_5_count   0.91630    0.06240  14.684   <2e-16 ***
## category_code_LT01_7_count   0.49132    0.15481   3.174   0.0016 ** 
## category_code_LT01_9_count   0.46177    0.22558   2.047   0.0412 *  
## category_code_LT01_12_count  0.18555    0.20490   0.906   0.3656    
## category_code_LT01_15_count  0.42335    0.75069   0.564   0.5730    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6246, Adjusted R-squared:   0.62 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 0.620482180256941 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0207 -0.7753 -0.0246  0.8824  4.0399 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00202    0.08723 114.660  < 2e-16 ***
## category_code_LT01_4_count   0.93709    0.07571  12.378  < 2e-16 ***
## category_code_LT01_5_count   0.91436    0.06238  14.658  < 2e-16 ***
## category_code_LT01_7_count   0.48954    0.15466   3.165  0.00165 ** 
## category_code_LT01_9_count   0.44985    0.22566   1.993  0.04676 *  
## category_code_LT01_12_count  0.18406    0.20475   0.899  0.36912    
## category_code_LT01_16_count  1.14320    1.16584   0.981  0.32728    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6251, Adjusted R-squared:  0.6205 
## F-statistic: 136.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 0.6191983486288 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0264 -0.7827 -0.0224  0.8515  4.0384 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00352    0.08745 114.389  < 2e-16 ***
## category_code_LT01_4_count   0.95241    0.07558  12.601  < 2e-16 ***
## category_code_LT01_5_count   0.92048    0.06246  14.736  < 2e-16 ***
## category_code_LT01_7_count   0.48433    0.15648   3.095  0.00208 ** 
## category_code_LT01_9_count   0.46884    0.22673   2.068  0.03918 *  
## category_code_LT01_13_count  0.07918    0.24642   0.321  0.74809    
## category_code_LT01_14_count  0.02598    0.32995   0.079  0.93728    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6238, Adjusted R-squared:  0.6192 
## F-statistic: 135.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 0.619448123822932 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0265 -0.7830 -0.0305  0.8500  4.0388 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00308    0.08734 114.534  < 2e-16 ***
## category_code_LT01_4_count   0.94533    0.07568  12.491  < 2e-16 ***
## category_code_LT01_5_count   0.92126    0.06217  14.819  < 2e-16 ***
## category_code_LT01_7_count   0.48650    0.15613   3.116  0.00194 ** 
## category_code_LT01_9_count   0.47210    0.22627   2.086  0.03745 *  
## category_code_LT01_13_count  0.08762    0.24678   0.355  0.72271    
## category_code_LT01_15_count  0.43130    0.75254   0.573  0.56682    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.624,  Adjusted R-squared:  0.6194 
## F-statistic: 135.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 0.619953123584433 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0254 -0.7809 -0.0225  0.8489  4.0386 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00329    0.08728 114.613   <2e-16 ***
## category_code_LT01_4_count   0.94917    0.07441  12.756   <2e-16 ***
## category_code_LT01_5_count   0.91925    0.06215  14.792   <2e-16 ***
## category_code_LT01_7_count   0.48475    0.15601   3.107   0.0020 ** 
## category_code_LT01_9_count   0.45992    0.22631   2.032   0.0427 *  
## category_code_LT01_13_count  0.08655    0.24629   0.351   0.7254    
## category_code_LT01_16_count  1.15626    1.16720   0.991   0.3224    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6245, Adjusted R-squared:   0.62 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 0.619354140670143 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0272 -0.7837 -0.0365  0.8687  4.0383 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00362    0.08743 114.417   <2e-16 ***
## category_code_LT01_4_count   0.94813    0.07613  12.454   <2e-16 ***
## category_code_LT01_5_count   0.92140    0.06243  14.758   <2e-16 ***
## category_code_LT01_7_count   0.49278    0.15523   3.174   0.0016 ** 
## category_code_LT01_9_count   0.46536    0.22614   2.058   0.0401 *  
## category_code_LT01_14_count  0.02284    0.32991   0.069   0.9448    
## category_code_LT01_15_count  0.41443    0.75133   0.552   0.5815    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.39 on 491 degrees of freedom
## Multiple R-squared:  0.6239, Adjusted R-squared:  0.6194 
## F-statistic: 135.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 0.619870159146758 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0260 -0.7814 -0.0272  0.8694  4.0378 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00405    0.08737 114.499  < 2e-16 ***
## category_code_LT01_4_count   0.95085    0.07504  12.672  < 2e-16 ***
## category_code_LT01_5_count   0.91907    0.06242  14.724  < 2e-16 ***
## category_code_LT01_7_count   0.49045    0.15508   3.163  0.00166 ** 
## category_code_LT01_9_count   0.45254    0.22625   2.000  0.04603 *  
## category_code_LT01_14_count  0.04214    0.33009   0.128  0.89847    
## category_code_LT01_16_count  1.15137    1.16832   0.985  0.32487    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.389 on 491 degrees of freedom
## Multiple R-squared:  0.6245, Adjusted R-squared:  0.6199 
## F-statistic: 136.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 0.620117027524057 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0261 -0.7821 -0.0356  0.8623  4.0384 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00345    0.08726 114.643  < 2e-16 ***
## category_code_LT01_4_count   0.94466    0.07501  12.594  < 2e-16 ***
## category_code_LT01_5_count   0.92018    0.06211  14.814  < 2e-16 ***
## category_code_LT01_7_count   0.49380    0.15476   3.191  0.00151 ** 
## category_code_LT01_9_count   0.45585    0.22573   2.019  0.04398 *  
## category_code_LT01_15_count  0.43478    0.75076   0.579  0.56277    
## category_code_LT01_16_count  1.16144    1.16680   0.995  0.32003    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.388 on 491 degrees of freedom
## Multiple R-squared:  0.6247, Adjusted R-squared:  0.6201 
## F-statistic: 136.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.626275636407859 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0064 -0.7640  0.0469  0.8959  3.6473 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98269    0.08995 110.975  < 2e-16 ***
## category_code_LT01_4_count   0.79313    0.08892   8.920  < 2e-16 ***
## category_code_LT01_5_count   0.92158    0.06171  14.933  < 2e-16 ***
## category_code_LT01_7_count   0.36908    0.15858   2.327 0.020349 *  
## category_code_LT01_10_count  0.12630    0.11171   1.131 0.258781    
## category_code_LT01_11_count  0.39402    0.11751   3.353 0.000861 ***
## category_code_LT01_12_count -0.01531    0.21162  -0.072 0.942356    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6308, Adjusted R-squared:  0.6263 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.626273343021669 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0060 -0.7664  0.0476  0.9004  3.6496 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98263    0.08995 110.980  < 2e-16 ***
## category_code_LT01_4_count   0.79260    0.08914   8.892  < 2e-16 ***
## category_code_LT01_5_count   0.92112    0.06147  14.985  < 2e-16 ***
## category_code_LT01_7_count   0.36896    0.15920   2.318 0.020885 *  
## category_code_LT01_10_count  0.12589    0.11165   1.127 0.260088    
## category_code_LT01_11_count  0.39152    0.11299   3.465 0.000576 ***
## category_code_LT01_13_count  0.01148    0.24366   0.047 0.962432    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6308, Adjusted R-squared:  0.6263 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.626274887060119 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0057 -0.7688  0.0475  0.8993  3.6482 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98204    0.09040 110.421  < 2e-16 ***
## category_code_LT01_4_count   0.79372    0.08971   8.847  < 2e-16 ***
## category_code_LT01_5_count   0.92157    0.06176  14.922  < 2e-16 ***
## category_code_LT01_7_count   0.37029    0.15851   2.336 0.019892 *  
## category_code_LT01_10_count  0.12755    0.11416   1.117 0.264437    
## category_code_LT01_11_count  0.39167    0.11294   3.468 0.000571 ***
## category_code_LT01_14_count -0.02175    0.33367  -0.065 0.948051    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6308, Adjusted R-squared:  0.6263 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.626294554492861 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0065 -0.7649  0.0469  0.9032  3.6518 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98296    0.08997 110.962  < 2e-16 ***
## category_code_LT01_4_count   0.79140    0.08930   8.862  < 2e-16 ***
## category_code_LT01_5_count   0.92134    0.06147  14.990  < 2e-16 ***
## category_code_LT01_7_count   0.37112    0.15849   2.342 0.019603 *  
## category_code_LT01_10_count  0.12438    0.11201   1.110 0.267373    
## category_code_LT01_11_count  0.39027    0.11323   3.447 0.000616 ***
## category_code_LT01_15_count  0.12993    0.74903   0.173 0.862358    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6308, Adjusted R-squared:  0.6263 
## F-statistic: 139.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.626868037313947 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0060 -0.7579  0.0486  0.9084  3.6563 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98364    0.08989 111.071  < 2e-16 ***
## category_code_LT01_4_count   0.79106    0.08883   8.905  < 2e-16 ***
## category_code_LT01_5_count   0.91965    0.06143  14.970  < 2e-16 ***
## category_code_LT01_7_count   0.37127    0.15818   2.347 0.019320 *  
## category_code_LT01_10_count  0.12119    0.11167   1.085 0.278367    
## category_code_LT01_11_count  0.38775    0.11294   3.433 0.000647 ***
## category_code_LT01_16_count  1.02503    1.15708   0.886 0.376118    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.376 on 491 degrees of freedom
## Multiple R-squared:  0.6314, Adjusted R-squared:  0.6269 
## F-statistic: 140.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 0.617729751744807 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0037 -0.7652  0.0067  0.8711  3.9102 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97794    0.09097 109.689  < 2e-16 ***
## category_code_LT01_4_count   0.95489    0.07577  12.602  < 2e-16 ***
## category_code_LT01_5_count   0.92463    0.06242  14.814  < 2e-16 ***
## category_code_LT01_7_count   0.50505    0.15594   3.239  0.00128 ** 
## category_code_LT01_10_count  0.13996    0.11292   1.239  0.21579    
## category_code_LT01_12_count  0.18001    0.20578   0.875  0.38212    
## category_code_LT01_13_count  0.03027    0.24641   0.123  0.90229    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6223, Adjusted R-squared:  0.6177 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 0.617730415750636 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0032 -0.7657 -0.0018  0.8806  3.9077 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97678    0.09143 109.124  < 2e-16 ***
## category_code_LT01_4_count   0.95728    0.07618  12.566  < 2e-16 ***
## category_code_LT01_5_count   0.92549    0.06267  14.767  < 2e-16 ***
## category_code_LT01_7_count   0.50831    0.15508   3.278  0.00112 ** 
## category_code_LT01_10_count  0.14325    0.11540   1.241  0.21507    
## category_code_LT01_12_count  0.18240    0.20615   0.885  0.37672    
## category_code_LT01_14_count -0.04270    0.33819  -0.126  0.89958    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6223, Adjusted R-squared:  0.6177 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 0.617862650164984 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0049 -0.7674 -0.0001  0.8730  3.9137 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97880    0.09097 109.691  < 2e-16 ***
## category_code_LT01_4_count   0.95033    0.07643  12.435  < 2e-16 ***
## category_code_LT01_5_count   0.92506    0.06240  14.824  < 2e-16 ***
## category_code_LT01_7_count   0.50944    0.15492   3.288  0.00108 ** 
## category_code_LT01_10_count  0.13598    0.11331   1.200  0.23070    
## category_code_LT01_12_count  0.18217    0.20570   0.886  0.37626    
## category_code_LT01_15_count  0.32574    0.75560   0.431  0.66658    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6179 
## F-statistic: 134.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 0.618512122884445 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0037 -0.7655  0.0189  0.8832  3.9150 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97915    0.09088 109.805  < 2e-16 ***
## category_code_LT01_4_count   0.95165    0.07539  12.623  < 2e-16 ***
## category_code_LT01_5_count   0.92290    0.06237  14.797  < 2e-16 ***
## category_code_LT01_7_count   0.50741    0.15471   3.280  0.00111 ** 
## category_code_LT01_10_count  0.13447    0.11293   1.191  0.23434    
## category_code_LT01_12_count  0.18089    0.20549   0.880  0.37914    
## category_code_LT01_16_count  1.18190    1.16907   1.011  0.31252    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.391 on 491 degrees of freedom
## Multiple R-squared:  0.6231, Adjusted R-squared:  0.6185 
## F-statistic: 135.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 0.617137364570649 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0076 -0.7665  0.0230  0.8683  3.9031 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97781    0.09149 109.059  < 2e-16 ***
## category_code_LT01_4_count   0.97047    0.07497  12.945  < 2e-16 ***
## category_code_LT01_5_count   0.93041    0.06247  14.895  < 2e-16 ***
## category_code_LT01_7_count   0.50704    0.15628   3.244  0.00126 ** 
## category_code_LT01_10_count  0.14648    0.11545   1.269  0.20512    
## category_code_LT01_13_count  0.03576    0.24654   0.145  0.88472    
## category_code_LT01_14_count -0.02229    0.33776  -0.066  0.94740    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6218, Adjusted R-squared:  0.6171 
## F-statistic: 134.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 0.617275287662025 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0090 -0.7688 -0.0128  0.8541  3.9081 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97928    0.09104 109.614  < 2e-16 ***
## category_code_LT01_4_count   0.96407    0.07507  12.843  < 2e-16 ***
## category_code_LT01_5_count   0.93031    0.06216  14.967  < 2e-16 ***
## category_code_LT01_7_count   0.50814    0.15607   3.256  0.00121 ** 
## category_code_LT01_10_count  0.14064    0.11329   1.241  0.21505    
## category_code_LT01_13_count  0.04246    0.24694   0.172  0.86356    
## category_code_LT01_15_count  0.32254    0.75750   0.426  0.67044    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617935717756749 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0078 -0.7692  0.0120  0.8700  3.9095 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97964    0.09095 109.730  < 2e-16 ***
## category_code_LT01_4_count   0.96513    0.07399  13.045  < 2e-16 ***
## category_code_LT01_5_count   0.92809    0.06213  14.939  < 2e-16 ***
## category_code_LT01_7_count   0.50596    0.15589   3.246  0.00125 ** 
## category_code_LT01_10_count  0.13900    0.11290   1.231  0.21886    
## category_code_LT01_13_count  0.04474    0.24641   0.182  0.85599    
## category_code_LT01_16_count  1.18830    1.17066   1.015  0.31058    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6179 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 0.617255649001162 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0088 -0.7682 -0.0154  0.8530  3.9064 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97865    0.09150 109.057  < 2e-16 ***
## category_code_LT01_4_count   0.96647    0.07552  12.797  < 2e-16 ***
## category_code_LT01_5_count   0.93092    0.06245  14.907  < 2e-16 ***
## category_code_LT01_7_count   0.51178    0.15525   3.297  0.00105 ** 
## category_code_LT01_10_count  0.14276    0.11582   1.233  0.21831    
## category_code_LT01_14_count -0.02232    0.33767  -0.066  0.94733    
## category_code_LT01_15_count  0.31430    0.75610   0.416  0.67783    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6219, Adjusted R-squared:  0.6173 
## F-statistic: 134.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617910103266594 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0079 -0.7691  0.0108  0.8699  3.9089 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97956    0.09141 109.168  < 2e-16 ***
## category_code_LT01_4_count   0.96678    0.07456  12.967  < 2e-16 ***
## category_code_LT01_5_count   0.92837    0.06243  14.871  < 2e-16 ***
## category_code_LT01_7_count   0.50934    0.15504   3.285  0.00109 ** 
## category_code_LT01_10_count  0.13965    0.11552   1.209  0.22730    
## category_code_LT01_14_count -0.00245    0.33800  -0.007  0.99422    
## category_code_LT01_16_count  1.18035    1.17213   1.007  0.31442    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6225, Adjusted R-squared:  0.6179 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 0.618066385382067 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0091 -0.7701 -0.0107  0.8610  3.9130 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98055    0.09095 109.731  < 2e-16 ***
## category_code_LT01_4_count   0.96100    0.07456  12.889  < 2e-16 ***
## category_code_LT01_5_count   0.92865    0.06211  14.953  < 2e-16 ***
## category_code_LT01_7_count   0.51154    0.15487   3.303  0.00103 ** 
## category_code_LT01_10_count  0.13501    0.11329   1.192  0.23396    
## category_code_LT01_15_count  0.33876    0.75566   0.448  0.65414    
## category_code_LT01_16_count  1.19730    1.17032   1.023  0.30679    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.392 on 491 degrees of freedom
## Multiple R-squared:  0.6227, Adjusted R-squared:  0.6181 
## F-statistic:   135 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.62530646550512 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0347 -0.7431  0.0443  0.9298  3.7549 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.010578   0.086612 115.580  < 2e-16 ***
## category_code_LT01_4_count   0.802061   0.088916   9.020  < 2e-16 ***
## category_code_LT01_5_count   0.922180   0.061800  14.922  < 2e-16 ***
## category_code_LT01_7_count   0.381126   0.159296   2.393 0.017106 *  
## category_code_LT01_11_count  0.398773   0.117614   3.391 0.000754 ***
## category_code_LT01_12_count -0.006499   0.211787  -0.031 0.975531    
## category_code_LT01_13_count  0.017103   0.243974   0.070 0.944140    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6253 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.625326166462659 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0347 -0.7456  0.0477  0.9182  3.7539 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.011273   0.086690 115.483  < 2e-16 ***
## category_code_LT01_4_count   0.800176   0.089669   8.924  < 2e-16 ***
## category_code_LT01_5_count   0.921254   0.062052  14.847  < 2e-16 ***
## category_code_LT01_7_count   0.380397   0.158733   2.396 0.016927 *  
## category_code_LT01_11_count  0.399211   0.117587   3.395 0.000742 ***
## category_code_LT01_12_count -0.009001   0.212340  -0.042 0.966207    
## category_code_LT01_14_count  0.057430   0.327597   0.175 0.860911    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6253 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.625356432043919 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0348 -0.7419  0.0433  0.9250  3.7566 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.010554   0.086605 115.589  < 2e-16 ***
## category_code_LT01_4_count   0.800012   0.089152   8.974  < 2e-16 ***
## category_code_LT01_5_count   0.922440   0.061791  14.928  < 2e-16 ***
## category_code_LT01_7_count   0.384258   0.158503   2.424  0.01570 *  
## category_code_LT01_11_count  0.396395   0.117972   3.360  0.00084 ***
## category_code_LT01_12_count -0.004248   0.211859  -0.020  0.98401    
## category_code_LT01_15_count  0.198423   0.747834   0.265  0.79087    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6254 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.625973379734815 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0335 -0.7373  0.0534  0.9217  3.7581 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.010535   0.086533 115.684  < 2e-16 ***
## category_code_LT01_4_count   0.800164   0.088601   9.031  < 2e-16 ***
## category_code_LT01_5_count   0.920548   0.061763  14.905  < 2e-16 ***
## category_code_LT01_7_count   0.383511   0.158213   2.424 0.015710 *  
## category_code_LT01_11_count  0.394232   0.117585   3.353 0.000862 ***
## category_code_LT01_12_count -0.004125   0.211568  -0.019 0.984453    
## category_code_LT01_16_count  1.085769   1.157165   0.938 0.348551    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.625328667167171 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0344 -0.7449  0.0482  0.9208  3.7551 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01115    0.08667 115.515  < 2e-16 ***
## category_code_LT01_4_count   0.79958    0.08993   8.891  < 2e-16 ***
## category_code_LT01_5_count   0.92095    0.06185  14.891  < 2e-16 ***
## category_code_LT01_7_count   0.37958    0.15937   2.382 0.017611 *  
## category_code_LT01_11_count  0.39758    0.11300   3.518 0.000474 ***
## category_code_LT01_13_count  0.01738    0.24393   0.071 0.943243    
## category_code_LT01_14_count  0.05662    0.32669   0.173 0.862478    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6253 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.625361784459626 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0346 -0.7403  0.0441  0.9268  3.7573 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01047    0.08659 115.613  < 2e-16 ***
## category_code_LT01_4_count   0.79929    0.08941   8.940  < 2e-16 ***
## category_code_LT01_5_count   0.92223    0.06155  14.985  < 2e-16 ***
## category_code_LT01_7_count   0.38300    0.15912   2.407 0.016454 *  
## category_code_LT01_11_count  0.39539    0.11333   3.489 0.000529 ***
## category_code_LT01_13_count  0.02105    0.24437   0.086 0.931405    
## category_code_LT01_15_count  0.20293    0.74881   0.271 0.786502    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6254 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.625981106978873 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0332 -0.7361  0.0541  0.9224  3.7589 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01045    0.08651 115.709  < 2e-16 ***
## category_code_LT01_4_count   0.79937    0.08883   8.999  < 2e-16 ***
## category_code_LT01_5_count   0.92031    0.06152  14.961  < 2e-16 ***
## category_code_LT01_7_count   0.38193    0.15888   2.404 0.016593 *  
## category_code_LT01_11_count  0.39323    0.11300   3.480 0.000546 ***
## category_code_LT01_13_count  0.02502    0.24386   0.103 0.918332    
## category_code_LT01_16_count  1.09018    1.15780   0.942 0.346866    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.625377983535622 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0346 -0.7448  0.0454  0.9145  3.7566 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01113    0.08666 115.524  < 2e-16 ***
## category_code_LT01_4_count   0.79764    0.09012   8.851  < 2e-16 ***
## category_code_LT01_5_count   0.92129    0.06184  14.899  < 2e-16 ***
## category_code_LT01_7_count   0.38267    0.15858   2.413 0.016182 *  
## category_code_LT01_11_count  0.39557    0.11326   3.493 0.000522 ***
## category_code_LT01_14_count  0.05529    0.32667   0.169 0.865663    
## category_code_LT01_15_count  0.19734    0.74742   0.264 0.791868    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6299, Adjusted R-squared:  0.6254 
## F-statistic: 139.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.626009566357366 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0332 -0.7422  0.0543  0.8906  3.7580 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01129    0.08659 115.623  < 2e-16 ***
## category_code_LT01_4_count   0.79707    0.08962   8.894  < 2e-16 ***
## category_code_LT01_5_count   0.91908    0.06181  14.869  < 2e-16 ***
## category_code_LT01_7_count   0.38142    0.15829   2.410 0.016335 *  
## category_code_LT01_11_count  0.39331    0.11295   3.482 0.000541 ***
## category_code_LT01_14_count  0.07151    0.32676   0.219 0.826870    
## category_code_LT01_16_count  1.09838    1.15843   0.948 0.343513    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6305, Adjusted R-squared:  0.626 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.626039268833578 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0335 -0.7352  0.0479  0.9018  3.7604 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01045    0.08651 115.720  < 2e-16 ***
## category_code_LT01_4_count   0.79730    0.08905   8.954  < 2e-16 ***
## category_code_LT01_5_count   0.92069    0.06150  14.970  < 2e-16 ***
## category_code_LT01_7_count   0.38573    0.15810   2.440 0.015047 *  
## category_code_LT01_11_count  0.39103    0.11327   3.452 0.000604 ***
## category_code_LT01_15_count  0.22021    0.74704   0.295 0.768292    
## category_code_LT01_16_count  1.09626    1.15752   0.947 0.344067    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.377 on 491 degrees of freedom
## Multiple R-squared:  0.6306, Adjusted R-squared:  0.626 
## F-statistic: 139.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.616548037956972 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0351 -0.7833  0.0230  0.8604  4.0325 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00936    0.08770 114.133  < 2e-16 ***
## category_code_LT01_4_count   0.96562    0.07636  12.645  < 2e-16 ***
## category_code_LT01_5_count   0.92462    0.06278  14.729  < 2e-16 ***
## category_code_LT01_7_count   0.51975    0.15601   3.331 0.000929 ***
## category_code_LT01_12_count  0.19061    0.20642   0.923 0.356248    
## category_code_LT01_13_count  0.03677    0.24676   0.149 0.881592    
## category_code_LT01_14_count  0.04473    0.33141   0.135 0.892689    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6212, Adjusted R-squared:  0.6165 
## F-statistic: 134.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.61676699853878 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0353 -0.7701  0.0168  0.8494  4.0331 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00874    0.08759 114.266  < 2e-16 ***
## category_code_LT01_4_count   0.95964    0.07652  12.540  < 2e-16 ***
## category_code_LT01_5_count   0.92571    0.06250  14.813  < 2e-16 ***
## category_code_LT01_7_count   0.52272    0.15561   3.359 0.000843 ***
## category_code_LT01_12_count  0.19391    0.20579   0.942 0.346526    
## category_code_LT01_13_count  0.04435    0.24710   0.179 0.857629    
## category_code_LT01_15_count  0.41274    0.75512   0.547 0.584908    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6168 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.617436912459892 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0337 -0.7775  0.0263  0.8521  4.0331 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00877    0.08751 114.366  < 2e-16 ***
## category_code_LT01_4_count   0.96206    0.07529  12.778  < 2e-16 ***
## category_code_LT01_5_count   0.92334    0.06247  14.781  < 2e-16 ***
## category_code_LT01_7_count   0.51996    0.15545   3.345 0.000886 ***
## category_code_LT01_12_count  0.19216    0.20560   0.935 0.350445    
## category_code_LT01_13_count  0.04537    0.24660   0.184 0.854088    
## category_code_LT01_16_count  1.25951    1.16989   1.077 0.282184    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616754164912461 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0355 -0.7786  0.0173  0.8729  4.0326 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00930    0.08768 114.164  < 2e-16 ***
## category_code_LT01_4_count   0.95964    0.07708  12.450  < 2e-16 ***
## category_code_LT01_5_count   0.92517    0.06275  14.743  < 2e-16 ***
## category_code_LT01_7_count   0.52466    0.15490   3.387 0.000763 ***
## category_code_LT01_12_count  0.19296    0.20630   0.935 0.350079    
## category_code_LT01_14_count  0.04161    0.33133   0.126 0.900108    
## category_code_LT01_15_count  0.40339    0.75389   0.535 0.592841    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6168 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.617437392960582 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0338 -0.7908  0.0277  0.8769  4.0323 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00956    0.08760 114.269  < 2e-16 ***
## category_code_LT01_4_count   0.96112    0.07601  12.645  < 2e-16 ***
## category_code_LT01_5_count   0.92246    0.06273  14.705  < 2e-16 ***
## category_code_LT01_7_count   0.52138    0.15472   3.370 0.000811 ***
## category_code_LT01_12_count  0.19034    0.20610   0.924 0.356199    
## category_code_LT01_14_count  0.06153    0.33140   0.186 0.852780    
## category_code_LT01_16_count  1.26279    1.17060   1.079 0.281228    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6221, Adjusted R-squared:  0.6174 
## F-statistic: 134.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617660395266191 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0340 -0.7681  0.0226  0.8645  4.0331 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00875    0.08749 114.401  < 2e-16 ***
## category_code_LT01_4_count   0.95576    0.07607  12.564  < 2e-16 ***
## category_code_LT01_5_count   0.92387    0.06244  14.796  < 2e-16 ***
## category_code_LT01_7_count   0.52552    0.15435   3.405 0.000716 ***
## category_code_LT01_12_count  0.19463    0.20548   0.947 0.343988    
## category_code_LT01_15_count  0.42665    0.75320   0.566 0.571342    
## category_code_LT01_16_count  1.26996    1.16930   1.086 0.277972    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.393 on 491 degrees of freedom
## Multiple R-squared:  0.6223, Adjusted R-squared:  0.6177 
## F-statistic: 134.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.616104667517727 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0409 -0.7556  0.0027  0.8385  4.0307 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01115    0.08773 114.118  < 2e-16 ***
## category_code_LT01_4_count   0.97336    0.07590  12.824  < 2e-16 ***
## category_code_LT01_5_count   0.93030    0.06255  14.872  < 2e-16 ***
## category_code_LT01_7_count   0.52265    0.15612   3.348 0.000878 ***
## category_code_LT01_13_count  0.05106    0.24724   0.207 0.836460    
## category_code_LT01_14_count  0.06547    0.33069   0.198 0.843148    
## category_code_LT01_15_count  0.40322    0.75579   0.534 0.593923    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.395 on 491 degrees of freedom
## Multiple R-squared:  0.6207, Adjusted R-squared:  0.6161 
## F-statistic: 133.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.616808200980307 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0391 -0.7811  0.0054  0.8384  4.0305 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01138    0.08765 114.226  < 2e-16 ***
## category_code_LT01_4_count   0.97451    0.07478  13.032  < 2e-16 ***
## category_code_LT01_5_count   0.92748    0.06253  14.832  < 2e-16 ***
## category_code_LT01_7_count   0.51922    0.15596   3.329 0.000937 ***
## category_code_LT01_13_count  0.05248    0.24672   0.213 0.831643    
## category_code_LT01_14_count  0.08528    0.33076   0.258 0.796638    
## category_code_LT01_16_count  1.27695    1.17224   1.089 0.276547    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6214, Adjusted R-squared:  0.6168 
## F-statistic: 134.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617008048898672 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0394 -0.7483  0.0068  0.8316  4.0316 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01033    0.08755 114.344  < 2e-16 ***
## category_code_LT01_4_count   0.97026    0.07465  12.997  < 2e-16 ***
## category_code_LT01_5_count   0.92944    0.06220  14.943  < 2e-16 ***
## category_code_LT01_7_count   0.52364    0.15555   3.366 0.000821 ***
## category_code_LT01_13_count  0.06022    0.24709   0.244 0.807552    
## category_code_LT01_15_count  0.42899    0.75516   0.568 0.570235    
## category_code_LT01_16_count  1.28143    1.17103   1.094 0.274372    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_7_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.617010015611792 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0396 -0.7555  0.0075  0.8577  4.0305 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01137    0.08762 114.257  < 2e-16 ***
## category_code_LT01_4_count   0.96902    0.07542  12.848  < 2e-16 ***
## category_code_LT01_5_count   0.92818    0.06250  14.850  < 2e-16 ***
## category_code_LT01_7_count   0.52540    0.15484   3.393 0.000747 ***
## category_code_LT01_14_count  0.08228    0.33067   0.249 0.803591    
## category_code_LT01_15_count  0.41563    0.75383   0.551 0.581637    
## category_code_LT01_16_count  1.28530    1.17164   1.097 0.273175    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.394 on 491 degrees of freedom
## Multiple R-squared:  0.6216, Adjusted R-squared:  0.617 
## F-statistic: 134.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count 0.62495067851954 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0048 -0.7670  0.0369  0.9165  3.6268 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97983    0.09013 110.733  < 2e-16 ***
## category_code_LT01_4_count   0.81752    0.08778   9.313  < 2e-16 ***
## category_code_LT01_5_count   0.92351    0.06238  14.805  < 2e-16 ***
## category_code_LT01_8_count  -0.13113    0.27326  -0.480   0.6315    
## category_code_LT01_9_count   0.42426    0.22572   1.880   0.0608 .  
## category_code_LT01_10_count  0.11983    0.11243   1.066   0.2870    
## category_code_LT01_11_count  0.43797    0.10996   3.983 7.83e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6295, Adjusted R-squared:  0.625 
## F-statistic:   139 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count 0.613469441700857 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0034 -0.8003 -0.0025  0.9252  3.9139 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97314    0.09148 109.018   <2e-16 ***
## category_code_LT01_4_count   1.02798    0.07016  14.652   <2e-16 ***
## category_code_LT01_5_count   0.93105    0.06351  14.659   <2e-16 ***
## category_code_LT01_8_count  -0.16663    0.27750  -0.600   0.5485    
## category_code_LT01_9_count   0.50656    0.22813   2.220   0.0268 *  
## category_code_LT01_10_count  0.14098    0.11408   1.236   0.2171    
## category_code_LT01_12_count  0.18621    0.20699   0.900   0.3688    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 491 degrees of freedom
## Multiple R-squared:  0.6181, Adjusted R-squared:  0.6135 
## F-statistic: 132.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count 0.613149093328045 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0064 -0.7779 -0.0118  0.9057  3.9112 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97359    0.09152 108.979   <2e-16 ***
## category_code_LT01_4_count   1.03510    0.06932  14.933   <2e-16 ***
## category_code_LT01_5_count   0.93471    0.06332  14.762   <2e-16 ***
## category_code_LT01_8_count  -0.14785    0.27789  -0.532   0.5949    
## category_code_LT01_9_count   0.51865    0.22861   2.269   0.0237 *  
## category_code_LT01_10_count  0.14300    0.11408   1.254   0.2106    
## category_code_LT01_13_count  0.15658    0.24695   0.634   0.5264    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6178, Adjusted R-squared:  0.6131 
## F-statistic: 132.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count 0.612832580478225 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0075 -0.7845 -0.0057  0.9059  3.9083 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.973688   0.092025 108.380   <2e-16 ***
## category_code_LT01_4_count   1.043345   0.069356  15.043   <2e-16 ***
## category_code_LT01_5_count   0.936205   0.063586  14.723   <2e-16 ***
## category_code_LT01_8_count  -0.157869   0.277570  -0.569   0.5698    
## category_code_LT01_9_count   0.509810   0.228492   2.231   0.0261 *  
## category_code_LT01_10_count  0.145531   0.116580   1.248   0.2125    
## category_code_LT01_14_count  0.005682   0.339454   0.017   0.9867    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6175, Adjusted R-squared:  0.6128 
## F-statistic: 132.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count 0.612941254807507 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0084 -0.7891  0.0008  0.9045  3.9113 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97427    0.09156 108.932   <2e-16 ***
## category_code_LT01_4_count   1.03912    0.06908  15.043   <2e-16 ***
## category_code_LT01_5_count   0.93663    0.06329  14.798   <2e-16 ***
## category_code_LT01_8_count  -0.15890    0.27754  -0.573   0.5672    
## category_code_LT01_9_count   0.51223    0.22834   2.243   0.0253 *  
## category_code_LT01_10_count  0.14226    0.11445   1.243   0.2144    
## category_code_LT01_15_count  0.28256    0.76025   0.372   0.7103    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6176, Adjusted R-squared:  0.6129 
## F-statistic: 132.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_16_count 0.613526717865031 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0079 -0.7882 -0.0119  0.9203  3.9120 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97478    0.09148 109.034   <2e-16 ***
## category_code_LT01_4_count   1.04033    0.06807  15.283   <2e-16 ***
## category_code_LT01_5_count   0.93518    0.06325  14.785   <2e-16 ***
## category_code_LT01_8_count  -0.17030    0.27763  -0.613   0.5399    
## category_code_LT01_9_count   0.50153    0.22826   2.197   0.0285 *  
## category_code_LT01_10_count  0.14121    0.11405   1.238   0.2162    
## category_code_LT01_16_count  1.10737    1.17901   0.939   0.3481    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 491 degrees of freedom
## Multiple R-squared:  0.6182, Adjusted R-squared:  0.6135 
## F-statistic: 132.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count 0.624097529865557 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0318 -0.7614  0.0246  0.9368  3.7244 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00614    0.08686 115.204  < 2e-16 ***
## category_code_LT01_4_count   0.82675    0.08750   9.448  < 2e-16 ***
## category_code_LT01_5_count   0.92446    0.06266  14.754  < 2e-16 ***
## category_code_LT01_8_count  -0.12355    0.27379  -0.451   0.6520    
## category_code_LT01_9_count   0.45376    0.22425   2.023   0.0436 *  
## category_code_LT01_11_count  0.44910    0.11425   3.931 9.68e-05 ***
## category_code_LT01_12_count -0.02917    0.21196  -0.138   0.8906    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6241 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count 0.624227137364267 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0300 -0.7621  0.0387  0.9151  3.7302 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00551    0.08683 115.233  < 2e-16 ***
## category_code_LT01_4_count   0.82216    0.08803   9.340  < 2e-16 ***
## category_code_LT01_5_count   0.92277    0.06248  14.769  < 2e-16 ***
## category_code_LT01_8_count  -0.11874    0.27388  -0.434   0.6648    
## category_code_LT01_9_count   0.45993    0.22464   2.047   0.0411 *  
## category_code_LT01_11_count  0.44171    0.11011   4.012 6.97e-05 ***
## category_code_LT01_13_count  0.10575    0.24370   0.434   0.6645    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6288, Adjusted R-squared:  0.6242 
## F-statistic: 138.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count 0.624114619720693 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0310 -0.7641  0.0370  0.9412  3.7272 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00669    0.08692 115.122  < 2e-16 ***
## category_code_LT01_4_count   0.82358    0.08862   9.293  < 2e-16 ***
## category_code_LT01_5_count   0.92257    0.06272  14.708  < 2e-16 ***
## category_code_LT01_8_count  -0.12593    0.27353  -0.460   0.6455    
## category_code_LT01_9_count   0.45091    0.22473   2.006   0.0454 *  
## category_code_LT01_11_count  0.44434    0.10992   4.043 6.14e-05 ***
## category_code_LT01_14_count  0.06648    0.32725   0.203   0.8391    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6241 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count 0.624116976682731 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0312 -0.7669  0.0374  0.9284  3.7288 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00587    0.08684 115.227  < 2e-16 ***
## category_code_LT01_4_count   0.82461    0.08792   9.379  < 2e-16 ***
## category_code_LT01_5_count   0.92398    0.06246  14.794  < 2e-16 ***
## category_code_LT01_8_count  -0.12599    0.27354  -0.461    0.645    
## category_code_LT01_9_count   0.45499    0.22430   2.029    0.043 *  
## category_code_LT01_11_count  0.44321    0.11015   4.024 6.64e-05 ***
## category_code_LT01_15_count  0.15755    0.74816   0.211    0.833    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6241 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_16_count 0.624644671495453 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0306 -0.7652  0.0393  0.9336  3.7299 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00610    0.08678 115.310  < 2e-16 ***
## category_code_LT01_4_count   0.82497    0.08743   9.435  < 2e-16 ***
## category_code_LT01_5_count   0.92284    0.06241  14.786  < 2e-16 ***
## category_code_LT01_8_count  -0.13683    0.27365  -0.500   0.6173    
## category_code_LT01_9_count   0.44599    0.22428   1.989   0.0473 *  
## category_code_LT01_11_count  0.44125    0.10989   4.015 6.87e-05 ***
## category_code_LT01_16_count  0.99567    1.16163   0.857   0.3918    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6292, Adjusted R-squared:  0.6246 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count 0.612604148317627 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0324 -0.7927  0.0203  0.9347  4.0387 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00315    0.08818 113.446   <2e-16 ***
## category_code_LT01_4_count   1.03297    0.07062  14.628   <2e-16 ***
## category_code_LT01_5_count   0.92970    0.06363  14.612   <2e-16 ***
## category_code_LT01_8_count  -0.15037    0.27823  -0.540   0.5891    
## category_code_LT01_9_count   0.55112    0.22684   2.430   0.0155 *  
## category_code_LT01_12_count  0.19409    0.20709   0.937   0.3491    
## category_code_LT01_13_count  0.16145    0.24706   0.654   0.5137    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6173, Adjusted R-squared:  0.6126 
## F-statistic:   132 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count 0.61230253544549 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0341 -0.7941  0.0138  0.9405  4.0373 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00457    0.08830 113.303   <2e-16 ***
## category_code_LT01_4_count   1.03861    0.07085  14.658   <2e-16 ***
## category_code_LT01_5_count   0.93005    0.06386  14.565   <2e-16 ***
## category_code_LT01_8_count  -0.16131    0.27790  -0.580   0.5619    
## category_code_LT01_9_count   0.53963    0.22709   2.376   0.0179 *  
## category_code_LT01_12_count  0.19532    0.20763   0.941   0.3473    
## category_code_LT01_14_count  0.07050    0.33319   0.212   0.8325    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.617,  Adjusted R-squared:  0.6123 
## F-statistic: 131.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count 0.612458913331242 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0342 -0.7994  0.0154  0.9323  4.0383 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00362    0.08819 113.435   <2e-16 ***
## category_code_LT01_4_count   1.03514    0.07062  14.658   <2e-16 ***
## category_code_LT01_5_count   0.93161    0.06360  14.648   <2e-16 ***
## category_code_LT01_8_count  -0.16244    0.27785  -0.585   0.5591    
## category_code_LT01_9_count   0.54454    0.22656   2.404   0.0166 *  
## category_code_LT01_12_count  0.19988    0.20703   0.965   0.3348    
## category_code_LT01_15_count  0.37356    0.75794   0.493   0.6223    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6171, Adjusted R-squared:  0.6125 
## F-statistic: 131.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_16_count 0.613048075653218 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0335 -0.7935  0.0136  0.9437  4.0379 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00394    0.08812 113.525   <2e-16 ***
## category_code_LT01_4_count   1.03766    0.06944  14.944   <2e-16 ***
## category_code_LT01_5_count   0.93002    0.06356  14.632   <2e-16 ***
## category_code_LT01_8_count  -0.17420    0.27794  -0.627   0.5311    
## category_code_LT01_9_count   0.53260    0.22659   2.350   0.0191 *  
## category_code_LT01_12_count  0.19884    0.20686   0.961   0.3369    
## category_code_LT01_16_count  1.17320    1.17860   0.995   0.3200    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6177, Adjusted R-squared:  0.613 
## F-statistic: 132.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count 0.611972874390796 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0376 -0.7953  0.0186  0.9019  4.0361 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00576    0.08832 113.289   <2e-16 ***
## category_code_LT01_4_count   1.04497    0.07023  14.878   <2e-16 ***
## category_code_LT01_5_count   0.93344    0.06370  14.653   <2e-16 ***
## category_code_LT01_8_count  -0.14145    0.27827  -0.508   0.6115    
## category_code_LT01_9_count   0.55205    0.22749   2.427   0.0156 *  
## category_code_LT01_13_count  0.16889    0.24712   0.683   0.4947    
## category_code_LT01_14_count  0.09293    0.33242   0.280   0.7799    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6167, Adjusted R-squared:  0.612 
## F-statistic: 131.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count 0.612127970400281 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0378 -0.7941  0.0165  0.9237  4.0373 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00454    0.08822 113.411   <2e-16 ***
## category_code_LT01_4_count   1.04207    0.06986  14.917   <2e-16 ***
## category_code_LT01_5_count   0.93548    0.06341  14.754   <2e-16 ***
## category_code_LT01_8_count  -0.14171    0.27821  -0.509   0.6107    
## category_code_LT01_9_count   0.55866    0.22695   2.462   0.0142 *  
## category_code_LT01_13_count  0.17720    0.24755   0.716   0.4745    
## category_code_LT01_15_count  0.39802    0.75967   0.524   0.6006    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6168, Adjusted R-squared:  0.6121 
## F-statistic: 131.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_16_count 0.612720946455445 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0370 -0.7944  0.0077  0.9337  4.0370 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00486    0.08815 113.501   <2e-16 ***
## category_code_LT01_4_count   1.04491    0.06856  15.241   <2e-16 ***
## category_code_LT01_5_count   0.93382    0.06337  14.737   <2e-16 ***
## category_code_LT01_8_count  -0.15373    0.27829  -0.552   0.5809    
## category_code_LT01_9_count   0.54633    0.22696   2.407   0.0164 *  
## category_code_LT01_13_count  0.17611    0.24698   0.713   0.4761    
## category_code_LT01_16_count  1.19521    1.17955   1.013   0.3114    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6174, Adjusted R-squared:  0.6127 
## F-statistic: 132.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count 0.611783378674645 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0397 -0.7959  0.0145  0.9008  4.0356 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00629    0.08834 113.274   <2e-16 ***
## category_code_LT01_4_count   1.04832    0.07006  14.964   <2e-16 ***
## category_code_LT01_5_count   0.93559    0.06367  14.694   <2e-16 ***
## category_code_LT01_8_count  -0.15364    0.27793  -0.553   0.5807    
## category_code_LT01_9_count   0.54524    0.22723   2.399   0.0168 *  
## category_code_LT01_14_count  0.09173    0.33252   0.276   0.7828    
## category_code_LT01_15_count  0.36156    0.75860   0.477   0.6339    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6165, Adjusted R-squared:  0.6118 
## F-statistic: 131.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_16_count 0.612408096035739 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0388 -0.7964  0.0060  0.9121  4.0350 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00683    0.08827 113.370   <2e-16 ***
## category_code_LT01_4_count   1.04956    0.06899  15.213   <2e-16 ***
## category_code_LT01_5_count   0.93361    0.06363  14.672   <2e-16 ***
## category_code_LT01_8_count  -0.16592    0.27802  -0.597   0.5509    
## category_code_LT01_9_count   0.53225    0.22729   2.342   0.0196 *  
## category_code_LT01_14_count  0.11120    0.33268   0.334   0.7383    
## category_code_LT01_16_count  1.19229    1.18117   1.009   0.3133    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6171, Adjusted R-squared:  0.6124 
## F-statistic: 131.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_9_count+category_code_LT01_15_count+category_code_LT01_16_count 0.61252305714574 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0391 -0.7963  0.0040  0.9297  4.0364 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00543    0.08817 113.485   <2e-16 ***
## category_code_LT01_4_count   1.04823    0.06840  15.326   <2e-16 ***
## category_code_LT01_5_count   0.93606    0.06334  14.779   <2e-16 ***
## category_code_LT01_8_count  -0.16640    0.27797  -0.599   0.5497    
## category_code_LT01_9_count   0.53927    0.22671   2.379   0.0178 *  
## category_code_LT01_15_count  0.38464    0.75809   0.507   0.6121    
## category_code_LT01_16_count  1.18778    1.17982   1.007   0.3146    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6172, Adjusted R-squared:  0.6125 
## F-statistic: 131.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.622280232314087 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0121 -0.7601  0.0333  0.9322  3.5788 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98064    0.09045 110.345  < 2e-16 ***
## category_code_LT01_4_count   0.83702    0.08751   9.565  < 2e-16 ***
## category_code_LT01_5_count   0.93283    0.06265  14.890  < 2e-16 ***
## category_code_LT01_8_count  -0.11173    0.27434  -0.407    0.684    
## category_code_LT01_10_count  0.14659    0.11203   1.309    0.191    
## category_code_LT01_11_count  0.46360    0.11414   4.062 5.67e-05 ***
## category_code_LT01_12_count -0.04067    0.21258  -0.191    0.848    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6268, Adjusted R-squared:  0.6223 
## F-statistic: 137.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.622308186914809 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0109 -0.7457  0.0356  0.9137  3.5860 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98048    0.09044 110.353  < 2e-16 ***
## category_code_LT01_4_count   0.83428    0.08795   9.486  < 2e-16 ***
## category_code_LT01_5_count   0.93133    0.06247  14.908  < 2e-16 ***
## category_code_LT01_8_count  -0.10975    0.27452  -0.400    0.689    
## category_code_LT01_10_count  0.14501    0.11201   1.295    0.196    
## category_code_LT01_11_count  0.45599    0.11002   4.145 4.01e-05 ***
## category_code_LT01_13_count  0.06589    0.24396   0.270    0.787    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6269, Adjusted R-squared:  0.6223 
## F-statistic: 137.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.622254778530659 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0116 -0.7463  0.0339  0.9324  3.5850 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98101    0.09091 109.792  < 2e-16 ***
## category_code_LT01_4_count   0.83592    0.08849   9.447  < 2e-16 ***
## category_code_LT01_5_count   0.93150    0.06275  14.845  < 2e-16 ***
## category_code_LT01_8_count  -0.11417    0.27411  -0.417    0.677    
## category_code_LT01_10_count  0.14444    0.11460   1.260    0.208    
## category_code_LT01_11_count  0.45759    0.10986   4.165 3.67e-05 ***
## category_code_LT01_14_count  0.01987    0.33503   0.059    0.953    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6268, Adjusted R-squared:  0.6223 
## F-statistic: 137.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.6222549795026 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0114 -0.7470  0.0346  0.9327  3.5847 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98059    0.09047 110.322  < 2e-16 ***
## category_code_LT01_4_count   0.83622    0.08785   9.519  < 2e-16 ***
## category_code_LT01_5_count   0.93194    0.06246  14.921  < 2e-16 ***
## category_code_LT01_8_count  -0.11418    0.27411  -0.417    0.677    
## category_code_LT01_10_count  0.14534    0.11232   1.294    0.196    
## category_code_LT01_11_count  0.45726    0.11006   4.155 3.84e-05 ***
## category_code_LT01_15_count  0.04624    0.75218   0.061    0.951    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6268, Adjusted R-squared:  0.6223 
## F-statistic: 137.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.622844059158684 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0116 -0.7413  0.0374  0.9112  3.5905 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98156    0.09039 110.433  < 2e-16 ***
## category_code_LT01_4_count   0.83515    0.08745   9.550  < 2e-16 ***
## category_code_LT01_5_count   0.93079    0.06241  14.915  < 2e-16 ***
## category_code_LT01_8_count  -0.12602    0.27422  -0.460    0.646    
## category_code_LT01_10_count  0.14129    0.11201   1.261    0.208    
## category_code_LT01_11_count  0.45393    0.10985   4.132 4.22e-05 ***
## category_code_LT01_16_count  1.02246    1.16469   0.878    0.380    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6274, Adjusted R-squared:  0.6228 
## F-statistic: 137.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 0.609762977376731 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0105 -0.7785  0.0273  0.9192  3.8794 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97361    0.09192 108.505   <2e-16 ***
## category_code_LT01_4_count   1.05712    0.06975  15.156   <2e-16 ***
## category_code_LT01_5_count   0.94063    0.06367  14.773   <2e-16 ***
## category_code_LT01_8_count  -0.14002    0.27920  -0.502    0.616    
## category_code_LT01_10_count  0.17191    0.11372   1.512    0.131    
## category_code_LT01_12_count  0.19091    0.20804   0.918    0.359    
## category_code_LT01_13_count  0.11618    0.24770   0.469    0.639    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6098 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 0.609590001075104 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0114 -0.7796  0.0254  0.9267  3.8785 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97401    0.09241 107.927   <2e-16 ***
## category_code_LT01_4_count   1.06207    0.06996  15.182   <2e-16 ***
## category_code_LT01_5_count   0.94131    0.06393  14.725   <2e-16 ***
## category_code_LT01_8_count  -0.14791    0.27877  -0.531    0.596    
## category_code_LT01_10_count  0.17239    0.11632   1.482    0.139    
## category_code_LT01_12_count  0.19318    0.20845   0.927    0.355    
## category_code_LT01_14_count  0.01658    0.34132   0.049    0.961    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6096 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 0.609673221734455 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0120 -0.7797  0.0259  0.9312  3.8804 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97421    0.09195 108.473   <2e-16 ***
## category_code_LT01_4_count   1.05881    0.06975  15.180   <2e-16 ***
## category_code_LT01_5_count   0.94189    0.06365  14.798   <2e-16 ***
## category_code_LT01_8_count  -0.14874    0.27875  -0.534    0.594    
## category_code_LT01_10_count  0.17043    0.11409   1.494    0.136    
## category_code_LT01_12_count  0.19504    0.20801   0.938    0.349    
## category_code_LT01_15_count  0.24973    0.76330   0.327    0.744    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6097 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 0.610421809897726 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0115 -0.7816  0.0225  0.9310  3.8826 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97491    0.09185 108.599   <2e-16 ***
## category_code_LT01_4_count   1.05846    0.06879  15.387   <2e-16 ***
## category_code_LT01_5_count   0.94016    0.06360  14.782   <2e-16 ***
## category_code_LT01_8_count  -0.16185    0.27880  -0.581    0.562    
## category_code_LT01_10_count  0.16780    0.11371   1.476    0.141    
## category_code_LT01_12_count  0.19444    0.20778   0.936    0.350    
## category_code_LT01_16_count  1.21245    1.18282   1.025    0.306    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6151, Adjusted R-squared:  0.6104 
## F-statistic: 130.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 0.609104056596427 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0152 -0.7731  0.0247  0.9197  3.8753 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97508    0.09247 107.879   <2e-16 ***
## category_code_LT01_4_count   1.07137    0.06911  15.502   <2e-16 ***
## category_code_LT01_5_count   0.94531    0.06377  14.825   <2e-16 ***
## category_code_LT01_8_count  -0.13071    0.27925  -0.468    0.640    
## category_code_LT01_10_count  0.17427    0.11639   1.497    0.135    
## category_code_LT01_13_count  0.12325    0.24780   0.497    0.619    
## category_code_LT01_14_count  0.03879    0.34079   0.114    0.909    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6138, Adjusted R-squared:  0.6091 
## F-statistic: 130.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 0.60918752303387 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0155 -0.7710  0.0237  0.9354  3.8763 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97471    0.09201 108.412   <2e-16 ***
## category_code_LT01_4_count   1.06873    0.06875  15.546   <2e-16 ***
## category_code_LT01_5_count   0.94633    0.06345  14.914   <2e-16 ***
## category_code_LT01_8_count  -0.13096    0.27921  -0.469    0.639    
## category_code_LT01_10_count  0.17375    0.11409   1.523    0.128    
## category_code_LT01_13_count  0.12852    0.24828   0.518    0.605    
## category_code_LT01_15_count  0.26267    0.76524   0.343    0.732    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6139, Adjusted R-squared:  0.6092 
## F-statistic: 130.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 0.609950140274509 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0150 -0.7756  0.0270  0.9383  3.8785 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97540    0.09191 108.540   <2e-16 ***
## category_code_LT01_4_count   1.06833    0.06770  15.780   <2e-16 ***
## category_code_LT01_5_count   0.94451    0.06340  14.898   <2e-16 ***
## category_code_LT01_8_count  -0.14407    0.27924  -0.516    0.606    
## category_code_LT01_10_count  0.17114    0.11370   1.505    0.133    
## category_code_LT01_13_count  0.13128    0.24765   0.530    0.596    
## category_code_LT01_16_count  1.22948    1.18414   1.038    0.300    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6147, Adjusted R-squared:   0.61 
## F-statistic: 130.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 0.608984256262039 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0168 -0.7772  0.0223  0.9274  3.8759 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97564    0.09250 107.841   <2e-16 ***
## category_code_LT01_4_count   1.07398    0.06897  15.572   <2e-16 ***
## category_code_LT01_5_count   0.94675    0.06374  14.853   <2e-16 ***
## category_code_LT01_8_count  -0.13965    0.27883  -0.501    0.617    
## category_code_LT01_10_count  0.17321    0.11674   1.484    0.139    
## category_code_LT01_14_count  0.03821    0.34084   0.112    0.911    
## category_code_LT01_15_count  0.23776    0.76387   0.311    0.756    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6137, Adjusted R-squared:  0.609 
## F-statistic:   130 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 0.609750624190189 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0166 -0.7804  0.0192  0.9315  3.8794 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97695    0.09241 107.966   <2e-16 ***
## category_code_LT01_4_count   1.07250    0.06808  15.753   <2e-16 ***
## category_code_LT01_5_count   0.94462    0.06370  14.830   <2e-16 ***
## category_code_LT01_8_count  -0.15311    0.27889  -0.549    0.583    
## category_code_LT01_10_count  0.16885    0.11645   1.450    0.148    
## category_code_LT01_14_count  0.05891    0.34114   0.173    0.863    
## category_code_LT01_16_count  1.22185    1.18604   1.030    0.303    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6098 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609820684640835 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0167 -0.7811  0.0243  0.9465  3.8792 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97603    0.09194 108.502   <2e-16 ***
## category_code_LT01_4_count   1.07097    0.06756  15.853   <2e-16 ***
## category_code_LT01_5_count   0.94605    0.06338  14.927   <2e-16 ***
## category_code_LT01_8_count  -0.15354    0.27885  -0.551    0.582    
## category_code_LT01_10_count  0.16989    0.11407   1.489    0.137    
## category_code_LT01_15_count  0.26223    0.76342   0.343    0.731    
## category_code_LT01_16_count  1.22230    1.18433   1.032    0.303    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6098 
## F-statistic: 130.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.621037019904149 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0444 -0.7353  0.0251  0.9002  3.7029 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01281    0.08714 114.899  < 2e-16 ***
## category_code_LT01_4_count   0.84686    0.08760   9.667  < 2e-16 ***
## category_code_LT01_5_count   0.93305    0.06278  14.863  < 2e-16 ***
## category_code_LT01_8_count  -0.09854    0.27517  -0.358    0.720    
## category_code_LT01_11_count  0.47062    0.11428   4.118 4.48e-05 ***
## category_code_LT01_12_count -0.03262    0.21284  -0.153    0.878    
## category_code_LT01_13_count  0.07565    0.24430   0.310    0.757    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6256, Adjusted R-squared:  0.621 
## F-statistic: 136.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.621055579540123 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0450 -0.7352  0.0262  0.9115  3.7003 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01433    0.08722 114.815  < 2e-16 ***
## category_code_LT01_4_count   0.84456    0.08838   9.556  < 2e-16 ***
## category_code_LT01_5_count   0.93163    0.06302  14.784  < 2e-16 ***
## category_code_LT01_8_count  -0.10457    0.27473  -0.381    0.704    
## category_code_LT01_11_count  0.47218    0.11412   4.137 4.13e-05 ***
## category_code_LT01_12_count -0.03676    0.21334  -0.172    0.863    
## category_code_LT01_14_count  0.11383    0.32868   0.346    0.729    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6256, Adjusted R-squared:  0.6211 
## F-statistic: 136.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.620982650469813 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0451 -0.7385  0.0238  0.9124  3.7023 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01300    0.08715 114.897  < 2e-16 ***
## category_code_LT01_4_count   0.84833    0.08755   9.689  < 2e-16 ***
## category_code_LT01_5_count   0.93381    0.06276  14.879  < 2e-16 ***
## category_code_LT01_8_count  -0.10404    0.27476  -0.379    0.705    
## category_code_LT01_11_count  0.47113    0.11444   4.117  4.5e-05 ***
## category_code_LT01_12_count -0.03043    0.21294  -0.143    0.886    
## category_code_LT01_15_count  0.11986    0.75148   0.159    0.873    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6256, Adjusted R-squared:  0.621 
## F-statistic: 136.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.62163611054989 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0443 -0.7347  0.0253  0.9068  3.7046 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01308    0.08707 114.997  < 2e-16 ***
## category_code_LT01_4_count   0.84761    0.08708   9.734  < 2e-16 ***
## category_code_LT01_5_count   0.93241    0.06271  14.869  < 2e-16 ***
## category_code_LT01_8_count  -0.11664    0.27486  -0.424    0.671    
## category_code_LT01_11_count  0.46777    0.11414   4.098 4.87e-05 ***
## category_code_LT01_12_count -0.02910    0.21266  -0.137    0.891    
## category_code_LT01_16_count  1.08915    1.16537   0.935    0.350    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6262, Adjusted R-squared:  0.6216 
## F-statistic: 137.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.621105808173853 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0434 -0.7346  0.0297  0.9053  3.7059 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01378    0.08720 114.842  < 2e-16 ***
## category_code_LT01_4_count   0.84155    0.08885   9.471  < 2e-16 ***
## category_code_LT01_5_count   0.93020    0.06287  14.795  < 2e-16 ***
## category_code_LT01_8_count  -0.10182    0.27490  -0.370    0.711    
## category_code_LT01_11_count  0.46483    0.10997   4.227 2.83e-05 ***
## category_code_LT01_13_count  0.07520    0.24425   0.308    0.758    
## category_code_LT01_14_count  0.11003    0.32784   0.336    0.737    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6257, Adjusted R-squared:  0.6211 
## F-statistic: 136.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.621045244139909 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0437 -0.7339  0.0267  0.9093  3.7075 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01253    0.08713 114.919  < 2e-16 ***
## category_code_LT01_4_count   0.84487    0.08807   9.593  < 2e-16 ***
## category_code_LT01_5_count   0.93247    0.06258  14.900  < 2e-16 ***
## category_code_LT01_8_count  -0.10089    0.27490  -0.367    0.714    
## category_code_LT01_11_count  0.46441    0.11021   4.214 2.99e-05 ***
## category_code_LT01_13_count  0.07800    0.24479   0.319    0.750    
## category_code_LT01_15_count  0.13908    0.75263   0.185    0.853    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6256, Adjusted R-squared:  0.621 
## F-statistic: 136.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.62170994213125 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0428 -0.7332  0.0290  0.9019  3.7096 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01261    0.08705 115.021  < 2e-16 ***
## category_code_LT01_4_count   0.84418    0.08754   9.643  < 2e-16 ***
## category_code_LT01_5_count   0.93102    0.06253  14.889  < 2e-16 ***
## category_code_LT01_8_count  -0.11322    0.27498  -0.412    0.681    
## category_code_LT01_11_count  0.46125    0.10995   4.195 3.24e-05 ***
## category_code_LT01_13_count  0.08265    0.24418   0.338    0.735    
## category_code_LT01_16_count  1.10410    1.16580   0.947    0.344    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6263, Adjusted R-squared:  0.6217 
## F-statistic: 137.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.621052688668928 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0442 -0.7346  0.0283  0.9169  3.7052 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01397    0.08720 114.840  < 2e-16 ***
## category_code_LT01_4_count   0.84304    0.08878   9.496  < 2e-16 ***
## category_code_LT01_5_count   0.93102    0.06286  14.812  < 2e-16 ***
## category_code_LT01_8_count  -0.10716    0.27450  -0.390    0.696    
## category_code_LT01_11_count  0.46564    0.11003   4.232 2.77e-05 ***
## category_code_LT01_14_count  0.10932    0.32787   0.333    0.739    
## category_code_LT01_15_count  0.12098    0.75104   0.161    0.872    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6256, Adjusted R-squared:  0.6211 
## F-statistic: 136.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.62173446430141 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0433 -0.7339  0.0308  0.9160  3.7072 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01425    0.08712 114.946  < 2e-16 ***
## category_code_LT01_4_count   0.84156    0.08834   9.526  < 2e-16 ***
## category_code_LT01_5_count   0.92933    0.06281  14.797  < 2e-16 ***
## category_code_LT01_8_count  -0.12019    0.27460  -0.438    0.662    
## category_code_LT01_11_count  0.46224    0.10979   4.210 3.04e-05 ***
## category_code_LT01_14_count  0.12549    0.32797   0.383    0.702    
## category_code_LT01_16_count  1.11344    1.16659   0.954    0.340    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6263, Adjusted R-squared:  0.6217 
## F-statistic: 137.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.621650375986363 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0437 -0.7339  0.0267  0.9122  3.7088 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01283    0.08705 115.018  < 2e-16 ***
## category_code_LT01_4_count   0.84566    0.08748   9.667  < 2e-16 ***
## category_code_LT01_5_count   0.93193    0.06251  14.908  < 2e-16 ***
## category_code_LT01_8_count  -0.11908    0.27461  -0.434    0.665    
## category_code_LT01_11_count  0.46205    0.11001   4.200 3.17e-05 ***
## category_code_LT01_15_count  0.14488    0.75076   0.193    0.847    
## category_code_LT01_16_count  1.09795    1.16579   0.942    0.347    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6262, Adjusted R-squared:  0.6217 
## F-statistic: 137.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.608056793756938 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0490 -0.7944  0.0069  0.9203  4.0289 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01295    0.08871 112.877   <2e-16 ***
## category_code_LT01_4_count   1.07077    0.07045  15.200   <2e-16 ***
## category_code_LT01_5_count   0.93949    0.06408  14.660   <2e-16 ***
## category_code_LT01_8_count  -0.13148    0.27975  -0.470    0.639    
## category_code_LT01_12_count  0.20076    0.20884   0.961    0.337    
## category_code_LT01_13_count  0.12820    0.24812   0.517    0.606    
## category_code_LT01_14_count  0.12399    0.33426   0.371    0.711    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.41 on 491 degrees of freedom
## Multiple R-squared:  0.6128, Adjusted R-squared:  0.6081 
## F-statistic: 129.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.608135702087958 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0493 -0.7948  0.0217  0.9395  4.0304 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01144    0.08861 112.977   <2e-16 ***
## category_code_LT01_4_count   1.06985    0.07006  15.270   <2e-16 ***
## category_code_LT01_5_count   0.94204    0.06380  14.765   <2e-16 ***
## category_code_LT01_8_count  -0.13139    0.27971  -0.470    0.639    
## category_code_LT01_12_count  0.20775    0.20823   0.998    0.319    
## category_code_LT01_13_count  0.13531    0.24855   0.544    0.586    
## category_code_LT01_15_count  0.37130    0.76349   0.486    0.627    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.41 on 491 degrees of freedom
## Multiple R-squared:  0.6129, Adjusted R-squared:  0.6081 
## F-statistic: 129.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.608934903762623 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0480 -0.8011  0.0152  0.9397  4.0303 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01159    0.08852 113.094   <2e-16 ***
## category_code_LT01_4_count   1.07078    0.06882  15.559   <2e-16 ***
## category_code_LT01_5_count   0.94002    0.06375  14.745   <2e-16 ***
## category_code_LT01_8_count  -0.14530    0.27974  -0.519    0.604    
## category_code_LT01_12_count  0.20644    0.20801   0.992    0.321    
## category_code_LT01_13_count  0.13633    0.24795   0.550    0.583    
## category_code_LT01_16_count  1.31885    1.18416   1.114    0.266    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6137, Adjusted R-squared:  0.6089 
## F-statistic:   130 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.608004880992926 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0503 -0.7971  0.0028  0.9259  4.0287 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01322    0.08871 112.875   <2e-16 ***
## category_code_LT01_4_count   1.07142    0.07053  15.192   <2e-16 ***
## category_code_LT01_5_count   0.94098    0.06406  14.689   <2e-16 ***
## category_code_LT01_8_count  -0.14145    0.27930  -0.506    0.613    
## category_code_LT01_12_count  0.20552    0.20876   0.984    0.325    
## category_code_LT01_14_count  0.12165    0.33431   0.364    0.716    
## category_code_LT01_15_count  0.34253    0.76225   0.449    0.653    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.41 on 491 degrees of freedom
## Multiple R-squared:  0.6127, Adjusted R-squared:  0.608 
## F-statistic: 129.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.608837402819971 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0491 -0.8032  0.0018  0.9274  4.0283 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01359    0.08862 112.999   <2e-16 ***
## category_code_LT01_4_count   1.07095    0.06950  15.409   <2e-16 ***
## category_code_LT01_5_count   0.93863    0.06401  14.664   <2e-16 ***
## category_code_LT01_8_count  -0.15581    0.27935  -0.558    0.577    
## category_code_LT01_12_count  0.20340    0.20852   0.975    0.330    
## category_code_LT01_14_count  0.14178    0.33433   0.424    0.672    
## category_code_LT01_16_count  1.32368    1.18519   1.117    0.265    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6136, Adjusted R-squared:  0.6088 
## F-statistic: 129.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.608881327579207 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0494 -0.8015  0.0109  0.9453  4.0300 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01189    0.08853 113.093   <2e-16 ***
## category_code_LT01_4_count   1.07128    0.06894  15.539   <2e-16 ***
## category_code_LT01_5_count   0.94157    0.06373  14.775   <2e-16 ***
## category_code_LT01_8_count  -0.15590    0.27933  -0.558    0.577    
## category_code_LT01_12_count  0.21141    0.20793   1.017    0.310    
## category_code_LT01_15_count  0.36923    0.76163   0.485    0.628    
## category_code_LT01_16_count  1.31488    1.18415   1.110    0.267    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6136, Adjusted R-squared:  0.6089 
## F-statistic:   130 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.6074954342564 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0548 -0.7984 -0.0073  0.9233  4.0271 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01477    0.08875 112.845   <2e-16 ***
## category_code_LT01_4_count   1.08061    0.06977  15.489   <2e-16 ***
## category_code_LT01_5_count   0.94514    0.06390  14.791   <2e-16 ***
## category_code_LT01_8_count  -0.12235    0.27976  -0.437    0.662    
## category_code_LT01_13_count  0.14297    0.24863   0.575    0.566    
## category_code_LT01_14_count  0.14647    0.33357   0.439    0.661    
## category_code_LT01_15_count  0.35890    0.76411   0.470    0.639    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.411 on 491 degrees of freedom
## Multiple R-squared:  0.6122, Adjusted R-squared:  0.6075 
## F-statistic: 129.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.608349729806784 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0534 -0.7973 -0.0048  0.9249  4.0267 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01513    0.08865 112.972   <2e-16 ***
## category_code_LT01_4_count   1.08005    0.06866  15.731   <2e-16 ***
## category_code_LT01_5_count   0.94267    0.06385  14.763   <2e-16 ***
## category_code_LT01_8_count  -0.13695    0.27978  -0.489    0.625    
## category_code_LT01_13_count  0.14438    0.24801   0.582    0.561    
## category_code_LT01_14_count  0.16677    0.33358   0.500    0.617    
## category_code_LT01_16_count  1.34866    1.18647   1.137    0.256    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6131, Adjusted R-squared:  0.6083 
## F-statistic: 129.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.608356399116035 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0540 -0.7979  0.0012  0.9370  4.0287 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01320    0.08857 113.050   <2e-16 ***
## category_code_LT01_4_count   1.08165    0.06788  15.934   <2e-16 ***
## category_code_LT01_5_count   0.94627    0.06353  14.896   <2e-16 ***
## category_code_LT01_8_count  -0.13590    0.27975  -0.486    0.627    
## category_code_LT01_13_count  0.15201    0.24849   0.612    0.541    
## category_code_LT01_15_count  0.38806    0.76355   0.508    0.612    
## category_code_LT01_16_count  1.33742    1.18555   1.128    0.260    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6131, Adjusted R-squared:  0.6084 
## F-statistic: 129.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_8_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.608252668444164 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0550 -0.8050 -0.0071  0.9350  4.0264 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01549    0.08866 112.965   <2e-16 ***
## category_code_LT01_4_count   1.08175    0.06859  15.771   <2e-16 ***
## category_code_LT01_5_count   0.94446    0.06382  14.798   <2e-16 ***
## category_code_LT01_8_count  -0.14772    0.27940  -0.529    0.597    
## category_code_LT01_14_count  0.16485    0.33364   0.494    0.621    
## category_code_LT01_15_count  0.35522    0.76221   0.466    0.641    
## category_code_LT01_16_count  1.34257    1.18650   1.132    0.258    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.41 on 491 degrees of freedom
## Multiple R-squared:  0.613,  Adjusted R-squared:  0.6083 
## F-statistic: 129.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count 0.624803708348644 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0017 -0.7613  0.0290  0.9176  3.6230 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97900    0.09012 110.726  < 2e-16 ***
## category_code_LT01_4_count   0.81666    0.08778   9.303  < 2e-16 ***
## category_code_LT01_5_count   0.92011    0.06194  14.855  < 2e-16 ***
## category_code_LT01_9_count   0.42029    0.22564   1.863  0.06311 .  
## category_code_LT01_10_count  0.11949    0.11250   1.062  0.28869    
## category_code_LT01_11_count  0.44527    0.11419   3.899  0.00011 ***
## category_code_LT01_12_count -0.04118    0.21168  -0.195  0.84584    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count 0.624910289440057 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0003 -0.7586  0.0377  0.9184  3.6320 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97886    0.09011 110.747  < 2e-16 ***
## category_code_LT01_4_count   0.81231    0.08826   9.204  < 2e-16 ***
## category_code_LT01_5_count   0.91831    0.06171  14.880  < 2e-16 ***
## category_code_LT01_9_count   0.42707    0.22612   1.889   0.0595 .  
## category_code_LT01_10_count  0.11704    0.11248   1.040   0.2986    
## category_code_LT01_11_count  0.43630    0.11016   3.961 8.58e-05 ***
## category_code_LT01_13_count  0.10246    0.24327   0.421   0.6738    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6294, Adjusted R-squared:  0.6249 
## F-statistic:   139 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count 0.62477515388465 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0006 -0.7622  0.0380  0.9208  3.6278 
## 
## Coefficients:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.978613   0.090581 110.163  < 2e-16 ***
## category_code_LT01_4_count   0.816582   0.088688   9.207  < 2e-16 ***
## category_code_LT01_5_count   0.919182   0.061992  14.827  < 2e-16 ***
## category_code_LT01_9_count   0.420850   0.225837   1.864    0.063 .  
## category_code_LT01_10_count  0.119248   0.114925   1.038    0.300    
## category_code_LT01_11_count  0.439284   0.109954   3.995 7.46e-05 ***
## category_code_LT01_14_count -0.007284   0.334177  -0.022    0.983    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count 0.62478531321211 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0010 -0.7613  0.0387  0.9226  3.6297 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97903    0.09014 110.707  < 2e-16 ***
## category_code_LT01_4_count   0.81534    0.08815   9.250  < 2e-16 ***
## category_code_LT01_5_count   0.91916    0.06170  14.896  < 2e-16 ***
## category_code_LT01_9_count   0.42150    0.22576   1.867   0.0625 .  
## category_code_LT01_10_count  0.11763    0.11282   1.043   0.2976    
## category_code_LT01_11_count  0.43844    0.11017   3.980 7.95e-05 ***
## category_code_LT01_15_count  0.08801    0.75001   0.117   0.9066    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6293, Adjusted R-squared:  0.6248 
## F-statistic: 138.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_16_count 0.625250436629683 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0008 -0.7587  0.0433  0.9172  3.6335 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97972    0.09007 110.797  < 2e-16 ***
## category_code_LT01_4_count   0.81510    0.08772   9.292  < 2e-16 ***
## category_code_LT01_5_count   0.91785    0.06168  14.881  < 2e-16 ***
## category_code_LT01_9_count   0.41397    0.22566   1.834   0.0672 .  
## category_code_LT01_10_count  0.11492    0.11246   1.022   0.3074    
## category_code_LT01_11_count  0.43631    0.10994   3.968 8.31e-05 ***
## category_code_LT01_16_count  0.91600    1.16034   0.789   0.4302    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.379 on 491 degrees of freedom
## Multiple R-squared:  0.6298, Adjusted R-squared:  0.6253 
## F-statistic: 139.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count 0.613508198500968 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9976 -0.7741  0.0032  0.9356  3.9194 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97198    0.09145 109.041   <2e-16 ***
## category_code_LT01_4_count   1.01948    0.07131  14.297   <2e-16 ***
## category_code_LT01_5_count   0.92441    0.06287  14.703   <2e-16 ***
## category_code_LT01_9_count   0.51145    0.22846   2.239   0.0256 *  
## category_code_LT01_10_count  0.13702    0.11414   1.201   0.2305    
## category_code_LT01_12_count  0.17796    0.20694   0.860   0.3902    
## category_code_LT01_13_count  0.15783    0.24654   0.640   0.5224    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 491 degrees of freedom
## Multiple R-squared:  0.6182, Adjusted R-squared:  0.6135 
## F-statistic: 132.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count 0.613187265992186 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9980 -0.7901  0.0018  0.9312  3.9157 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97140    0.09196 108.429   <2e-16 ***
## category_code_LT01_4_count   1.02822    0.07126  14.430   <2e-16 ***
## category_code_LT01_5_count   0.92583    0.06314  14.664   <2e-16 ***
## category_code_LT01_9_count   0.50281    0.22830   2.202   0.0281 *  
## category_code_LT01_10_count  0.14090    0.11658   1.209   0.2274    
## category_code_LT01_12_count  0.18245    0.20738   0.880   0.3794    
## category_code_LT01_14_count -0.01566    0.34002  -0.046   0.9633    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6179, Adjusted R-squared:  0.6132 
## F-statistic: 132.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count 0.613299726228343 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9992 -0.7835  0.0116  0.9216  3.9199 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97258    0.09150 108.994   <2e-16 ***
## category_code_LT01_4_count   1.02298    0.07124  14.360   <2e-16 ***
## category_code_LT01_5_count   0.92582    0.06287  14.726   <2e-16 ***
## category_code_LT01_9_count   0.50463    0.22815   2.212   0.0274 *  
## category_code_LT01_10_count  0.13599    0.11452   1.187   0.2356    
## category_code_LT01_12_count  0.18314    0.20693   0.885   0.3766    
## category_code_LT01_15_count  0.28930    0.75996   0.381   0.7036    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.618,  Adjusted R-squared:  0.6133 
## F-statistic: 132.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_16_count 0.613840943921752 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.9983 -0.7822  0.0077  0.9384  3.9205 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97294    0.09142 109.090   <2e-16 ***
## category_code_LT01_4_count   1.02443    0.07021  14.590   <2e-16 ***
## category_code_LT01_5_count   0.92405    0.06284  14.704   <2e-16 ***
## category_code_LT01_9_count   0.49386    0.22811   2.165   0.0309 *  
## category_code_LT01_10_count  0.13511    0.11412   1.184   0.2370    
## category_code_LT01_12_count  0.18215    0.20676   0.881   0.3788    
## category_code_LT01_16_count  1.07458    1.17719   0.913   0.3618    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 491 degrees of freedom
## Multiple R-squared:  0.6185, Adjusted R-squared:  0.6138 
## F-statistic: 132.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count 0.612926257532182 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0018 -0.7692 -0.0078  0.9197  3.9140 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.972571   0.091987 108.413   <2e-16 ***
## category_code_LT01_4_count  1.033864   0.070615  14.641   <2e-16 ***
## category_code_LT01_5_count  0.929564   0.062925  14.773   <2e-16 ***
## category_code_LT01_9_count  0.515134   0.228786   2.252   0.0248 *  
## category_code_LT01_10_count 0.141342   0.116641   1.212   0.2262    
## category_code_LT01_13_count 0.164038   0.246628   0.665   0.5063    
## category_code_LT01_14_count 0.005273   0.339406   0.016   0.9876    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6176, Adjusted R-squared:  0.6129 
## F-statistic: 132.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count 0.613059181254973 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0027 -0.7814 -0.0007  0.8992  3.9176 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97324    0.09152 108.968   <2e-16 ***
## category_code_LT01_4_count   1.02878    0.07049  14.595   <2e-16 ***
## category_code_LT01_5_count   0.92993    0.06262  14.851   <2e-16 ***
## category_code_LT01_9_count   0.51814    0.22865   2.266   0.0239 *  
## category_code_LT01_10_count  0.13752    0.11453   1.201   0.2304    
## category_code_LT01_13_count  0.17077    0.24713   0.691   0.4899    
## category_code_LT01_15_count  0.31308    0.76178   0.411   0.6813    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6177, Adjusted R-squared:  0.6131 
## F-statistic: 132.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_16_count 0.613611204108539 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0017 -0.7674 -0.0103  0.9253  3.9180 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97357    0.09145 109.065   <2e-16 ***
## category_code_LT01_4_count   1.03040    0.06936  14.856   <2e-16 ***
## category_code_LT01_5_count   0.92807    0.06259  14.828   <2e-16 ***
## category_code_LT01_9_count   0.50701    0.22855   2.218    0.027 *  
## category_code_LT01_10_count  0.13680    0.11411   1.199    0.231    
## category_code_LT01_13_count  0.17147    0.24654   0.696    0.487    
## category_code_LT01_16_count  1.09931    1.17815   0.933    0.351    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 491 degrees of freedom
## Multiple R-squared:  0.6183, Adjusted R-squared:  0.6136 
## F-statistic: 132.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count 0.612683011812017 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0035 -0.7846  0.0027  0.9137  3.9141 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 9.973134   0.092037 108.360   <2e-16 ***
## category_code_LT01_4_count  1.038339   0.070402  14.749   <2e-16 ***
## category_code_LT01_5_count  0.931179   0.062917  14.800   <2e-16 ***
## category_code_LT01_9_count  0.507988   0.228505   2.223   0.0267 *  
## category_code_LT01_10_count 0.140751   0.117018   1.203   0.2296    
## category_code_LT01_14_count 0.004697   0.339512   0.014   0.9890    
## category_code_LT01_15_count 0.278114   0.760470   0.366   0.7147    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6174, Adjusted R-squared:  0.6127 
## F-statistic:   132 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_16_count 0.61323424751969 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0029 -0.7736 -0.0051  0.9229  3.9158 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97404    0.09197 108.452   <2e-16 ***
## category_code_LT01_4_count   1.03878    0.06945  14.957   <2e-16 ***
## category_code_LT01_5_count   0.92906    0.06290  14.770   <2e-16 ***
## category_code_LT01_9_count   0.49673    0.22848   2.174   0.0302 *  
## category_code_LT01_10_count  0.13835    0.11669   1.186   0.2363    
## category_code_LT01_14_count  0.02331    0.33992   0.069   0.9453    
## category_code_LT01_16_count  1.07780    1.18039   0.913   0.3616    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6179, Adjusted R-squared:  0.6132 
## F-statistic: 132.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_10_count+category_code_LT01_15_count+category_code_LT01_16_count 0.613352586662806 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0035 -0.7815 -0.0024  0.9218  3.9182 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97418    0.09150 109.010   <2e-16 ***
## category_code_LT01_4_count   1.03496    0.06914  14.969   <2e-16 ***
## category_code_LT01_5_count   0.92977    0.06258  14.857   <2e-16 ***
## category_code_LT01_9_count   0.49969    0.22829   2.189   0.0291 *  
## category_code_LT01_10_count  0.13608    0.11450   1.188   0.2352    
## category_code_LT01_15_count  0.29925    0.76015   0.394   0.6940    
## category_code_LT01_16_count  1.08680    1.17847   0.922   0.3569    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.4 on 491 degrees of freedom
## Multiple R-squared:  0.618,  Adjusted R-squared:  0.6134 
## F-statistic: 132.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.624103856088928 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0269 -0.7532  0.0378  0.9165  3.7269 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00465    0.08682 115.233  < 2e-16 ***
## category_code_LT01_4_count   0.82108    0.08800   9.330  < 2e-16 ***
## category_code_LT01_5_count   0.91958    0.06202  14.827  < 2e-16 ***
## category_code_LT01_9_count   0.45663    0.22455   2.034 0.042537 *  
## category_code_LT01_11_count  0.44773    0.11438   3.914 0.000103 ***
## category_code_LT01_12_count -0.03472    0.21177  -0.164 0.869822    
## category_code_LT01_13_count  0.11204    0.24340   0.460 0.645491    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6286, Adjusted R-squared:  0.6241 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.623975096838337 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0278 -0.7556  0.0346  0.9437  3.7235 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00583    0.08692 115.111  < 2e-16 ***
## category_code_LT01_4_count   0.82261    0.08861   9.283  < 2e-16 ***
## category_code_LT01_5_count   0.91919    0.06226  14.764  < 2e-16 ***
## category_code_LT01_9_count   0.44694    0.22464   1.990   0.0472 *  
## category_code_LT01_11_count  0.45088    0.11420   3.948 9.02e-05 ***
## category_code_LT01_12_count -0.03658    0.21233  -0.172   0.8633    
## category_code_LT01_14_count  0.06859    0.32812   0.209   0.8345    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.624 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.623972061217594 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0279 -0.7618  0.0364  0.9355  3.7256 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00494    0.08683 115.220   <2e-16 ***
## category_code_LT01_4_count   0.82378    0.08794   9.368   <2e-16 ***
## category_code_LT01_5_count   0.92051    0.06201  14.844   <2e-16 ***
## category_code_LT01_9_count   0.45107    0.22420   2.012   0.0448 *  
## category_code_LT01_11_count  0.44918    0.11452   3.922   0.0001 ***
## category_code_LT01_12_count -0.03203    0.21190  -0.151   0.8799    
## category_code_LT01_15_count  0.14921    0.74862   0.199   0.8421    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.624 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.624470662026761 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0270 -0.7558  0.0395  0.9353  3.7268 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00506    0.08678 115.298  < 2e-16 ***
## category_code_LT01_4_count   0.82398    0.08744   9.423  < 2e-16 ***
## category_code_LT01_5_count   0.91904    0.06199  14.827  < 2e-16 ***
## category_code_LT01_9_count   0.44205    0.22420   1.972 0.049205 *  
## category_code_LT01_11_count  0.44729    0.11420   3.917 0.000103 ***
## category_code_LT01_12_count -0.03166    0.21165  -0.150 0.881156    
## category_code_LT01_16_count  0.96519    1.16053   0.832 0.405993    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.624112858549608 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0260 -0.7497  0.0420  0.9177  3.7303 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00511    0.08689 115.153  < 2e-16 ***
## category_code_LT01_4_count   0.81795    0.08912   9.178  < 2e-16 ***
## category_code_LT01_5_count   0.91750    0.06207  14.783  < 2e-16 ***
## category_code_LT01_9_count   0.45381    0.22505   2.016   0.0443 *  
## category_code_LT01_11_count  0.44221    0.11013   4.016 6.86e-05 ***
## category_code_LT01_13_count  0.11143    0.24338   0.458   0.6473    
## category_code_LT01_14_count  0.06433    0.32722   0.197   0.8442    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6241 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.62412586473013 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0261 -0.7588  0.0415  0.8971  3.7321 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00429    0.08680 115.257  < 2e-16 ***
## category_code_LT01_4_count   0.81849    0.08850   9.249  < 2e-16 ***
## category_code_LT01_5_count   0.91887    0.06178  14.873  < 2e-16 ***
## category_code_LT01_9_count   0.45814    0.22462   2.040   0.0419 *  
## category_code_LT01_11_count  0.44075    0.11039   3.993 7.54e-05 ***
## category_code_LT01_13_count  0.11539    0.24393   0.473   0.6364    
## category_code_LT01_15_count  0.17686    0.74979   0.236   0.8136    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6287, Adjusted R-squared:  0.6241 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.624634322183792 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0251 -0.7459  0.0479  0.8956  3.7332 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00441    0.08674 115.337  < 2e-16 ***
## category_code_LT01_4_count   0.81887    0.08795   9.311  < 2e-16 ***
## category_code_LT01_5_count   0.91733    0.06175  14.854  < 2e-16 ***
## category_code_LT01_9_count   0.44895    0.22458   1.999   0.0462 *  
## category_code_LT01_11_count  0.43903    0.11011   3.987  7.7e-05 ***
## category_code_LT01_13_count  0.11833    0.24334   0.486   0.6270    
## category_code_LT01_16_count  0.98557    1.16085   0.849   0.3963    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.6292, Adjusted R-squared:  0.6246 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.623983649874717 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0270 -0.7582  0.0403  0.9372  3.7287 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00541    0.08690 115.141  < 2e-16 ***
## category_code_LT01_4_count   0.82065    0.08903   9.218  < 2e-16 ***
## category_code_LT01_5_count   0.91852    0.06206  14.801  < 2e-16 ***
## category_code_LT01_9_count   0.44831    0.22469   1.995   0.0466 *  
## category_code_LT01_11_count  0.44402    0.11016   4.031 6.44e-05 ***
## category_code_LT01_14_count  0.06379    0.32730   0.195   0.8455    
## category_code_LT01_15_count  0.15122    0.74827   0.202   0.8399    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.381 on 491 degrees of freedom
## Multiple R-squared:  0.6285, Adjusted R-squared:  0.624 
## F-statistic: 138.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.624498025816454 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0260 -0.7474  0.0467  0.9372  3.7298 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00571    0.08684 115.223  < 2e-16 ***
## category_code_LT01_4_count   0.82020    0.08858   9.259  < 2e-16 ***
## category_code_LT01_5_count   0.91676    0.06204  14.778  < 2e-16 ***
## category_code_LT01_9_count   0.43844    0.22472   1.951   0.0516 .  
## category_code_LT01_11_count  0.44204    0.10991   4.022 6.68e-05 ***
## category_code_LT01_14_count  0.07898    0.32750   0.241   0.8095    
## category_code_LT01_16_count  0.98153    1.16201   0.845   0.3987    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.624493490050205 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0262 -0.7527  0.0470  0.9199  3.7315 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00474    0.08675 115.324  < 2e-16 ***
## category_code_LT01_4_count   0.82161    0.08787   9.351  < 2e-16 ***
## category_code_LT01_5_count   0.91842    0.06175  14.874  < 2e-16 ***
## category_code_LT01_9_count   0.44324    0.22424   1.977   0.0486 *  
## category_code_LT01_11_count  0.44089    0.11015   4.003 7.23e-05 ***
## category_code_LT01_15_count  0.17094    0.74802   0.229   0.8193    
## category_code_LT01_16_count  0.97454    1.16092   0.839   0.4016    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.38 on 491 degrees of freedom
## Multiple R-squared:  0.629,  Adjusted R-squared:  0.6245 
## F-statistic: 138.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.61240707514397 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0276 -0.7920  0.0325  0.9449  4.0393 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00255    0.08825 113.343   <2e-16 ***
## category_code_LT01_4_count   1.02921    0.07206  14.283   <2e-16 ***
## category_code_LT01_5_count   0.92352    0.06322  14.608   <2e-16 ***
## category_code_LT01_9_count   0.54433    0.22731   2.395    0.017 *  
## category_code_LT01_12_count  0.18667    0.20757   0.899    0.369    
## category_code_LT01_13_count  0.16905    0.24672   0.685    0.494    
## category_code_LT01_14_count  0.06852    0.33313   0.206    0.837    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6171, Adjusted R-squared:  0.6124 
## F-statistic: 131.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.612594970622625 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0276 -0.7911  0.0354  0.9328  4.0403 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00158    0.08814 113.478   <2e-16 ***
## category_code_LT01_4_count   1.02472    0.07199  14.235   <2e-16 ***
## category_code_LT01_5_count   0.92497    0.06295  14.694   <2e-16 ***
## category_code_LT01_9_count   0.54968    0.22678   2.424   0.0157 *  
## category_code_LT01_12_count  0.19099    0.20696   0.923   0.3565    
## category_code_LT01_13_count  0.17724    0.24714   0.717   0.4736    
## category_code_LT01_15_count  0.40208    0.75923   0.530   0.5966    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6173, Adjusted R-squared:  0.6126 
## F-statistic:   132 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.613142214349799 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0264 -0.7911  0.0283  0.9481  4.0401 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00180    0.08807 113.561   <2e-16 ***
## category_code_LT01_4_count   1.02778    0.07069  14.539   <2e-16 ***
## category_code_LT01_5_count   0.92299    0.06293  14.668   <2e-16 ***
## category_code_LT01_9_count   0.53735    0.22682   2.369   0.0182 *  
## category_code_LT01_12_count  0.18955    0.20680   0.917   0.3598    
## category_code_LT01_13_count  0.17652    0.24660   0.716   0.4745    
## category_code_LT01_16_count  1.16305    1.17761   0.988   0.3238    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6178, Adjusted R-squared:  0.6131 
## F-statistic: 132.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.61222052695852 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0290 -0.7925  0.0277  0.9428  4.0390 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00291    0.08827 113.323   <2e-16 ***
## category_code_LT01_4_count   1.03198    0.07204  14.324   <2e-16 ***
## category_code_LT01_5_count   0.92511    0.06321  14.635   <2e-16 ***
## category_code_LT01_9_count   0.53708    0.22702   2.366   0.0184 *  
## category_code_LT01_12_count  0.19240    0.20754   0.927   0.3543    
## category_code_LT01_14_count  0.06643    0.33324   0.199   0.8421    
## category_code_LT01_15_count  0.36601    0.75818   0.483   0.6295    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6169, Adjusted R-squared:  0.6122 
## F-statistic: 131.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.612790296574112 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0279 -0.7926  0.0224  0.9464  4.0385 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00334    0.08820 113.411   <2e-16 ***
## category_code_LT01_4_count   1.03358    0.07097  14.564   <2e-16 ***
## category_code_LT01_5_count   0.92284    0.06319  14.604   <2e-16 ***
## category_code_LT01_9_count   0.52417    0.22711   2.308   0.0214 *  
## category_code_LT01_12_count  0.19019    0.20737   0.917   0.3595    
## category_code_LT01_14_count  0.08544    0.33341   0.256   0.7979    
## category_code_LT01_16_count  1.15286    1.17916   0.978   0.3287    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6175, Adjusted R-squared:  0.6128 
## F-statistic: 132.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.612944707656222 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0280 -0.7918  0.0231  0.9460  4.0397 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00220    0.08809 113.540   <2e-16 ***
## category_code_LT01_4_count   1.03051    0.07071  14.575   <2e-16 ***
## category_code_LT01_5_count   0.92463    0.06292  14.696   <2e-16 ***
## category_code_LT01_9_count   0.52980    0.22654   2.339   0.0198 *  
## category_code_LT01_12_count  0.19546    0.20677   0.945   0.3450    
## category_code_LT01_15_count  0.38750    0.75767   0.511   0.6093    
## category_code_LT01_16_count  1.15305    1.17776   0.979   0.3281    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.401 on 491 degrees of freedom
## Multiple R-squared:  0.6176, Adjusted R-squared:  0.6129 
## F-statistic: 132.2 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.611979158187983 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0330 -0.7938  0.0270  0.9044  4.0377 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00420    0.08828 113.328   <2e-16 ***
## category_code_LT01_4_count   1.03691    0.07153  14.497   <2e-16 ***
## category_code_LT01_5_count   0.92899    0.06300  14.746   <2e-16 ***
## category_code_LT01_9_count   0.55089    0.22743   2.422   0.0158 *  
## category_code_LT01_13_count  0.18393    0.24722   0.744   0.4573    
## category_code_LT01_14_count  0.08861    0.33242   0.267   0.7899    
## category_code_LT01_15_count  0.39215    0.75986   0.516   0.6060    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.403 on 491 degrees of freedom
## Multiple R-squared:  0.6167, Adjusted R-squared:  0.612 
## F-statistic: 131.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.612563373237062 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0318 -0.7942  0.0185  0.9105  4.0372 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00463    0.08821 113.418   <2e-16 ***
## category_code_LT01_4_count   1.03868    0.07035  14.764   <2e-16 ***
## category_code_LT01_5_count   0.92658    0.06298  14.712   <2e-16 ***
## category_code_LT01_9_count   0.53748    0.22749   2.363   0.0185 *  
## category_code_LT01_13_count  0.18344    0.24666   0.744   0.4574    
## category_code_LT01_14_count  0.10795    0.33258   0.325   0.7456    
## category_code_LT01_16_count  1.18424    1.18005   1.004   0.3161    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6172, Adjusted R-squared:  0.6126 
## F-statistic:   132 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.612717220471157 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0320 -0.7928  0.0187  0.9351  4.0387 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00323    0.08811 113.536   <2e-16 ***
## category_code_LT01_4_count   1.03616    0.06994  14.814   <2e-16 ***
## category_code_LT01_5_count   0.92891    0.06266  14.824   <2e-16 ***
## category_code_LT01_9_count   0.54490    0.22690   2.402   0.0167 *  
## category_code_LT01_13_count  0.19216    0.24712   0.778   0.4372    
## category_code_LT01_15_count  0.41623    0.75937   0.548   0.5839    
## category_code_LT01_16_count  1.18278    1.17872   1.003   0.3161    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.6174, Adjusted R-squared:  0.6127 
## F-statistic: 132.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_9_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.6123209716505 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0335 -0.7946  0.0149  0.9073  4.0368 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.00509    0.08823 113.391   <2e-16 ***
## category_code_LT01_4_count   1.04259    0.07019  14.854   <2e-16 ***
## category_code_LT01_5_count   0.92848    0.06297  14.744   <2e-16 ***
## category_code_LT01_9_count   0.52976    0.22724   2.331   0.0201 *  
## category_code_LT01_14_count  0.10637    0.33270   0.320   0.7493    
## category_code_LT01_15_count  0.37589    0.75827   0.496   0.6203    
## category_code_LT01_16_count  1.17249    1.18025   0.993   0.3210    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.402 on 491 degrees of freedom
## Multiple R-squared:  0.617,  Adjusted R-squared:  0.6123 
## F-statistic: 131.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count 0.622220112673812 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0084 -0.7434  0.0378  0.9129  3.5820 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97983    0.09043 110.357  < 2e-16 ***
## category_code_LT01_4_count   0.83328    0.08791   9.479  < 2e-16 ***
## category_code_LT01_5_count   0.92865    0.06198  14.983  < 2e-16 ***
## category_code_LT01_10_count  0.14464    0.11205   1.291    0.197    
## category_code_LT01_11_count  0.46335    0.11424   4.056 5.81e-05 ***
## category_code_LT01_12_count -0.04523    0.21242  -0.213    0.831    
## category_code_LT01_13_count  0.07215    0.24361   0.296    0.767    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6268, Adjusted R-squared:  0.6222 
## F-statistic: 137.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count 0.622156278316441 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0090 -0.7463  0.0354  0.9335  3.5810 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98042    0.09091 109.787  < 2e-16 ***
## category_code_LT01_4_count   0.83497    0.08846   9.439  < 2e-16 ***
## category_code_LT01_5_count   0.92866    0.06225  14.918  < 2e-16 ***
## category_code_LT01_10_count  0.14386    0.11461   1.255    0.210    
## category_code_LT01_11_count  0.46516    0.11410   4.077 5.32e-05 ***
## category_code_LT01_12_count -0.04538    0.21287  -0.213    0.831    
## category_code_LT01_14_count  0.02314    0.33578   0.069    0.945    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6267, Adjusted R-squared:  0.6222 
## F-statistic: 137.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count 0.622154522797174 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0088 -0.7489  0.0349  0.9338  3.5805 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97988    0.09046 110.326  < 2e-16 ***
## category_code_LT01_4_count   0.83548    0.08784   9.511  < 2e-16 ***
## category_code_LT01_5_count   0.92911    0.06198  14.991  < 2e-16 ***
## category_code_LT01_10_count  0.14508    0.11238   1.291    0.197    
## category_code_LT01_11_count  0.46472    0.11436   4.064 5.62e-05 ***
## category_code_LT01_12_count -0.04404    0.21255  -0.207    0.836    
## category_code_LT01_15_count  0.03738    0.75270   0.050    0.960    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6267, Adjusted R-squared:  0.6222 
## F-statistic: 137.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_16_count 0.622712357924092 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0086 -0.7394  0.0372  0.9120  3.5866 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98075    0.09038 110.431  < 2e-16 ***
## category_code_LT01_4_count   0.83422    0.08744   9.541  < 2e-16 ***
## category_code_LT01_5_count   0.92756    0.06195  14.973  < 2e-16 ***
## category_code_LT01_10_count  0.14092    0.11206   1.257    0.209    
## category_code_LT01_11_count  0.46127    0.11410   4.043 6.14e-05 ***
## category_code_LT01_12_count -0.04230    0.21227  -0.199    0.842    
## category_code_LT01_16_count  0.99304    1.16352   0.853    0.394    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6273, Adjusted R-squared:  0.6227 
## F-statistic: 137.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count 0.622187791658881 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0077 -0.7412  0.0437  0.9126  3.5887 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98015    0.09089 109.805  < 2e-16 ***
## category_code_LT01_4_count   0.83216    0.08890   9.361  < 2e-16 ***
## category_code_LT01_5_count   0.92714    0.06206  14.940  < 2e-16 ***
## category_code_LT01_10_count  0.14243    0.11463   1.242    0.215    
## category_code_LT01_11_count  0.45671    0.11003   4.151  3.9e-05 ***
## category_code_LT01_13_count  0.07160    0.24361   0.294    0.769    
## category_code_LT01_14_count  0.01932    0.33505   0.058    0.954    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6267, Adjusted R-squared:  0.6222 
## F-statistic: 137.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count 0.622189823574808 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0076 -0.7383  0.0434  0.9130  3.5886 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97977    0.09045 110.335  < 2e-16 ***
## category_code_LT01_4_count   0.83227    0.08831   9.424  < 2e-16 ***
## category_code_LT01_5_count   0.92758    0.06175  15.021  < 2e-16 ***
## category_code_LT01_10_count  0.14313    0.11236   1.274    0.203    
## category_code_LT01_11_count  0.45624    0.11025   4.138 4.12e-05 ***
## category_code_LT01_13_count  0.07277    0.24417   0.298    0.766    
## category_code_LT01_15_count  0.05824    0.75398   0.077    0.938    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6268, Adjusted R-squared:  0.6222 
## F-statistic: 137.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_16_count 0.622763301399159 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0073 -0.7296  0.0472  0.8943  3.5945 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98061    0.09037 110.443  < 2e-16 ***
## category_code_LT01_4_count   0.83098    0.08786   9.458  < 2e-16 ***
## category_code_LT01_5_count   0.92598    0.06172  15.003  < 2e-16 ***
## category_code_LT01_10_count  0.13908    0.11204   1.241    0.215    
## category_code_LT01_11_count  0.45299    0.11002   4.117  4.5e-05 ***
## category_code_LT01_13_count  0.07931    0.24358   0.326    0.745    
## category_code_LT01_16_count  1.00980    1.16416   0.867    0.386    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6273, Adjusted R-squared:  0.6228 
## F-statistic: 137.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count 0.622123844773361 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0081 -0.7399  0.0375  0.9341  3.5871 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98020    0.09092 109.772  < 2e-16 ***
## category_code_LT01_4_count   0.83432    0.08882   9.393  < 2e-16 ***
## category_code_LT01_5_count   0.92764    0.06206  14.949  < 2e-16 ***
## category_code_LT01_10_count  0.14287    0.11496   1.243    0.215    
## category_code_LT01_11_count  0.45819    0.11006   4.163 3.71e-05 ***
## category_code_LT01_14_count  0.01859    0.33508   0.055    0.956    
## category_code_LT01_15_count  0.04315    0.75229   0.057    0.954    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.384 on 491 degrees of freedom
## Multiple R-squared:  0.6267, Adjusted R-squared:  0.6221 
## F-statistic: 137.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_16_count 0.622690706070593 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0081 -0.7310  0.0450  0.9112  3.5940 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98154    0.09084 109.875  < 2e-16 ***
## category_code_LT01_4_count   0.83243    0.08844   9.413  < 2e-16 ***
## category_code_LT01_5_count   0.92579    0.06203  14.924  < 2e-16 ***
## category_code_LT01_10_count  0.13749    0.11471   1.199    0.231    
## category_code_LT01_11_count  0.45493    0.10985   4.141 4.06e-05 ***
## category_code_LT01_14_count  0.03602    0.33544   0.107    0.915    
## category_code_LT01_16_count  1.00337    1.16563   0.861    0.390    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6272, Adjusted R-squared:  0.6227 
## F-statistic: 137.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_11_count+category_code_LT01_15_count+category_code_LT01_16_count 0.622687508993818 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0078 -0.7327  0.0436  0.9120  3.5930 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.98072    0.09040 110.409  < 2e-16 ***
## category_code_LT01_4_count   0.83318    0.08778   9.491  < 2e-16 ***
## category_code_LT01_5_count   0.92656    0.06172  15.013  < 2e-16 ***
## category_code_LT01_10_count  0.13937    0.11237   1.240    0.215    
## category_code_LT01_11_count  0.45452    0.11005   4.130 4.26e-05 ***
## category_code_LT01_15_count  0.06457    0.75213   0.086    0.932    
## category_code_LT01_16_count  0.99911    1.16414   0.858    0.391    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.383 on 491 degrees of freedom
## Multiple R-squared:  0.6272, Adjusted R-squared:  0.6227 
## F-statistic: 137.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.609565027419017 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0064 -0.7730  0.0241  0.9198  3.8828 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97298    0.09239 107.944   <2e-16 ***
## category_code_LT01_4_count   1.05559    0.07097  14.874   <2e-16 ***
## category_code_LT01_5_count   0.93560    0.06327  14.788   <2e-16 ***
## category_code_LT01_10_count  0.16937    0.11636   1.455    0.146    
## category_code_LT01_12_count  0.18630    0.20842   0.894    0.372    
## category_code_LT01_13_count  0.12369    0.24733   0.500    0.617    
## category_code_LT01_14_count  0.01692    0.34134   0.050    0.960    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6096 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.60966306599522 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0070 -0.7731  0.0262  0.9195  3.8851 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97322    0.09193 108.492   <2e-16 ***
## category_code_LT01_4_count   1.05174    0.07088  14.838   <2e-16 ***
## category_code_LT01_5_count   0.93615    0.06298  14.865   <2e-16 ***
## category_code_LT01_10_count  0.16708    0.11414   1.464    0.144    
## category_code_LT01_12_count  0.18813    0.20795   0.905    0.366    
## category_code_LT01_13_count  0.12922    0.24780   0.521    0.602    
## category_code_LT01_15_count  0.27126    0.76485   0.355    0.723    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6144, Adjusted R-squared:  0.6097 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.610381718464307 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0060 -0.7739  0.0235  0.9197  3.8873 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97376    0.09183 108.613   <2e-16 ***
## category_code_LT01_4_count   1.05157    0.06982  15.061   <2e-16 ***
## category_code_LT01_5_count   0.93395    0.06295  14.837   <2e-16 ***
## category_code_LT01_10_count  0.16462    0.11376   1.447    0.149    
## category_code_LT01_12_count  0.18700    0.20773   0.900    0.368    
## category_code_LT01_13_count  0.13231    0.24721   0.535    0.593    
## category_code_LT01_16_count  1.20074    1.18217   1.016    0.310    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6151, Adjusted R-squared:  0.6104 
## F-statistic: 130.8 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.609448590929432 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0076 -0.7740  0.0204  0.9336  3.8838 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97346    0.09243 107.908   <2e-16 ***
## category_code_LT01_4_count   1.05772    0.07098  14.901   <2e-16 ***
## category_code_LT01_5_count   0.93663    0.06326  14.805   <2e-16 ***
## category_code_LT01_10_count  0.16805    0.11673   1.440    0.151    
## category_code_LT01_12_count  0.19041    0.20839   0.914    0.361    
## category_code_LT01_14_count  0.01581    0.34138   0.046    0.963    
## category_code_LT01_15_count  0.24580    0.76349   0.322    0.748    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6142, Adjusted R-squared:  0.6094 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.610163189802738 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0070 -0.7746  0.0001  0.9341  3.8872 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97459    0.09234 108.025   <2e-16 ***
## category_code_LT01_4_count   1.05658    0.07008  15.077   <2e-16 ***
## category_code_LT01_5_count   0.93414    0.06324  14.772   <2e-16 ***
## category_code_LT01_10_count  0.16393    0.11644   1.408    0.160    
## category_code_LT01_12_count  0.18866    0.20817   0.906    0.365    
## category_code_LT01_14_count  0.03589    0.34168   0.105    0.916    
## category_code_LT01_16_count  1.18624    1.18395   1.002    0.317    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.6149, Adjusted R-squared:  0.6102 
## F-statistic: 130.6 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.610253576738659 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0073 -0.7747  0.0148  0.9385  3.8884 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97431    0.09186 108.576   <2e-16 ***
## category_code_LT01_4_count   1.05372    0.06984  15.087   <2e-16 ***
## category_code_LT01_5_count   0.93505    0.06294  14.856   <2e-16 ***
## category_code_LT01_10_count  0.16308    0.11414   1.429    0.154    
## category_code_LT01_12_count  0.19138    0.20772   0.921    0.357    
## category_code_LT01_15_count  0.26968    0.76306   0.353    0.724    
## category_code_LT01_16_count  1.19181    1.18223   1.008    0.314    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.406 on 491 degrees of freedom
## Multiple R-squared:  0.615,  Adjusted R-squared:  0.6103 
## F-statistic: 130.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.609022363070979 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0119 -0.7673  0.0333  0.9226  3.8808 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97472    0.09247 107.869   <2e-16 ***
## category_code_LT01_4_count   1.06603    0.07021  15.184   <2e-16 ***
## category_code_LT01_5_count   0.94107    0.06305  14.927   <2e-16 ***
## category_code_LT01_10_count  0.16964    0.11680   1.452    0.147    
## category_code_LT01_13_count  0.13550    0.24792   0.547    0.585    
## category_code_LT01_14_count  0.03811    0.34082   0.112    0.911    
## category_code_LT01_15_count  0.26122    0.76541   0.341    0.733    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6137, Adjusted R-squared:  0.609 
## F-statistic:   130 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.609762013329837 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0112 -0.7654  0.0303  0.9222  3.8843 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97584    0.09238 107.991   <2e-16 ***
## category_code_LT01_4_count   1.06471    0.06923  15.379   <2e-16 ***
## category_code_LT01_5_count   0.93844    0.06302  14.890   <2e-16 ***
## category_code_LT01_10_count  0.16547    0.11650   1.420    0.156    
## category_code_LT01_13_count  0.13897    0.24732   0.562    0.574    
## category_code_LT01_14_count  0.05846    0.34112   0.171    0.864    
## category_code_LT01_16_count  1.21302    1.18530   1.023    0.307    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6145, Adjusted R-squared:  0.6098 
## F-statistic: 130.4 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609850523923121 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0113 -0.7647  0.0305  0.9300  3.8844 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97500    0.09191 108.528   <2e-16 ***
## category_code_LT01_4_count   1.06248    0.06883  15.435   <2e-16 ***
## category_code_LT01_5_count   0.93984    0.06268  14.994   <2e-16 ***
## category_code_LT01_10_count  0.16606    0.11413   1.455    0.146    
## category_code_LT01_13_count  0.14466    0.24782   0.584    0.560    
## category_code_LT01_15_count  0.28702    0.76501   0.375    0.708    
## category_code_LT01_16_count  1.21563    1.18365   1.027    0.305    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6146, Adjusted R-squared:  0.6099 
## F-statistic: 130.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_10_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.609602316252611 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0126 -0.7717  0.0280  0.9215  3.8850 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  9.97635    0.09242 107.947   <2e-16 ***
## category_code_LT01_4_count   1.06778    0.06911  15.450   <2e-16 ***
## category_code_LT01_5_count   0.93973    0.06302  14.912   <2e-16 ***
## category_code_LT01_10_count  0.16437    0.11687   1.406    0.160    
## category_code_LT01_14_count  0.05747    0.34118   0.168    0.866    
## category_code_LT01_15_count  0.25867    0.76361   0.339    0.735    
## category_code_LT01_16_count  1.20221    1.18540   1.014    0.311    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.407 on 491 degrees of freedom
## Multiple R-squared:  0.6143, Adjusted R-squared:  0.6096 
## F-statistic: 130.3 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count 0.621028843926765 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0410 -0.7320  0.0331  0.9121  3.7019 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01313    0.08718 114.851  < 2e-16 ***
## category_code_LT01_4_count   0.84045    0.08880   9.465  < 2e-16 ***
## category_code_LT01_5_count   0.92765    0.06236  14.877  < 2e-16 ***
## category_code_LT01_11_count  0.47150    0.11424   4.127 4.31e-05 ***
## category_code_LT01_12_count -0.04125    0.21317  -0.194    0.847    
## category_code_LT01_13_count  0.08098    0.24391   0.332    0.740    
## category_code_LT01_14_count  0.11273    0.32867   0.343    0.732    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6256, Adjusted R-squared:  0.621 
## F-statistic: 136.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count 0.620962024446693 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0412 -0.7318  0.0313  0.9096  3.7041 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01180    0.08711 114.932  < 2e-16 ***
## category_code_LT01_4_count   0.84393    0.08804   9.586  < 2e-16 ***
## category_code_LT01_5_count   0.92983    0.06208  14.978  < 2e-16 ***
## category_code_LT01_11_count  0.47023    0.11458   4.104 4.75e-05 ***
## category_code_LT01_12_count -0.03487    0.21275  -0.164    0.870    
## category_code_LT01_13_count  0.08349    0.24445   0.342    0.733    
## category_code_LT01_15_count  0.13271    0.75305   0.176    0.860    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.621 
## F-statistic: 136.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_16_count 0.621599263280035 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0399 -0.7307  0.0334  0.9096  3.7064 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01175    0.08704 115.028  < 2e-16 ***
## category_code_LT01_4_count   0.84305    0.08751   9.634  < 2e-16 ***
## category_code_LT01_5_count   0.92797    0.06205  14.955  < 2e-16 ***
## category_code_LT01_11_count  0.46709    0.11426   4.088 5.08e-05 ***
## category_code_LT01_12_count -0.03417    0.21248  -0.161    0.872    
## category_code_LT01_13_count  0.08869    0.24387   0.364    0.716    
## category_code_LT01_16_count  1.07874    1.16461   0.926    0.355    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6262, Adjusted R-squared:  0.6216 
## F-statistic: 137.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count 0.62096114020577 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0416 -0.7324  0.0315  0.9172  3.7013 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01326    0.08719 114.844  < 2e-16 ***
## category_code_LT01_4_count   0.84219    0.08875   9.489  < 2e-16 ***
## category_code_LT01_5_count   0.92826    0.06235  14.887  < 2e-16 ***
## category_code_LT01_11_count  0.47229    0.11438   4.129 4.28e-05 ***
## category_code_LT01_12_count -0.03920    0.21329  -0.184    0.854    
## category_code_LT01_14_count  0.11171    0.32872   0.340    0.734    
## category_code_LT01_15_count  0.11273    0.75148   0.150    0.881    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6255, Adjusted R-squared:  0.621 
## F-statistic: 136.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_16_count 0.621612658323325 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0402 -0.7315  0.0340  0.9196  3.7034 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01340    0.08711 114.945  < 2e-16 ***
## category_code_LT01_4_count   0.84055    0.08832   9.517  < 2e-16 ***
## category_code_LT01_5_count   0.92617    0.06233  14.860  < 2e-16 ***
## category_code_LT01_11_count  0.46900    0.11409   4.111 4.62e-05 ***
## category_code_LT01_12_count -0.03896    0.21299  -0.183    0.855    
## category_code_LT01_14_count  0.12719    0.32880   0.387    0.699    
## category_code_LT01_16_count  1.08558    1.16523   0.932    0.352    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6262, Adjusted R-squared:  0.6216 
## F-statistic: 137.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_12_count+category_code_LT01_15_count+category_code_LT01_16_count 0.621522807119258 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0405 -0.7313  0.0324  0.9170  3.7057 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01191    0.08704 115.020  < 2e-16 ***
## category_code_LT01_4_count   0.84477    0.08748   9.656  < 2e-16 ***
## category_code_LT01_5_count   0.92865    0.06205  14.967  < 2e-16 ***
## category_code_LT01_11_count  0.46785    0.11441   4.089 5.06e-05 ***
## category_code_LT01_12_count -0.03187    0.21259  -0.150    0.881    
## category_code_LT01_15_count  0.13656    0.75121   0.182    0.856    
## category_code_LT01_16_count  1.07004    1.16452   0.919    0.359    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.386 on 491 degrees of freedom
## Multiple R-squared:  0.6261, Adjusted R-squared:  0.6215 
## F-statistic:   137 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.621024476841858 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0400 -0.7311  0.0354  0.9167  3.7075 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01269    0.08716 114.878  < 2e-16 ***
## category_code_LT01_4_count   0.83865    0.08926   9.395  < 2e-16 ***
## category_code_LT01_5_count   0.92685    0.06216  14.910  < 2e-16 ***
## category_code_LT01_11_count  0.46413    0.11024   4.210 3.03e-05 ***
## category_code_LT01_13_count  0.08319    0.24442   0.340    0.734    
## category_code_LT01_14_count  0.10763    0.32785   0.328    0.743    
## category_code_LT01_15_count  0.13421    0.75266   0.178    0.859    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.387 on 491 degrees of freedom
## Multiple R-squared:  0.6256, Adjusted R-squared:  0.621 
## F-statistic: 136.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.621688573329644 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0386 -0.7301  0.0370  0.9086  3.7096 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01282    0.08708 114.980  < 2e-16 ***
## category_code_LT01_4_count   0.83701    0.08879   9.427  < 2e-16 ***
## category_code_LT01_5_count   0.92467    0.06213  14.882  < 2e-16 ***
## category_code_LT01_11_count  0.46087    0.10998   4.190  3.3e-05 ***
## category_code_LT01_13_count  0.08858    0.24383   0.363    0.717    
## category_code_LT01_14_count  0.12348    0.32795   0.377    0.707    
## category_code_LT01_16_count  1.10217    1.16584   0.945    0.345    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6263, Adjusted R-squared:  0.6217 
## F-statistic: 137.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.621613828700473 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0390 -0.7301  0.0351  0.9082  3.7113 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01143    0.08702 115.052  < 2e-16 ***
## category_code_LT01_4_count   0.84075    0.08798   9.556  < 2e-16 ***
## category_code_LT01_5_count   0.92728    0.06181  15.001  < 2e-16 ***
## category_code_LT01_11_count  0.46042    0.11023   4.177  3.5e-05 ***
## category_code_LT01_13_count  0.09164    0.24440   0.375    0.708    
## category_code_LT01_15_count  0.15918    0.75242   0.212    0.833    
## category_code_LT01_16_count  1.08845    1.16514   0.934    0.351    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6262, Adjusted R-squared:  0.6216 
## F-statistic: 137.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_11_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.621612869653304 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0393 -0.7307  0.0385  0.9226  3.7087 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01299    0.08709 114.973  < 2e-16 ***
## category_code_LT01_4_count   0.83878    0.08873   9.453  < 2e-16 ***
## category_code_LT01_5_count   0.92543    0.06213  14.895  < 2e-16 ***
## category_code_LT01_11_count  0.46196    0.11003   4.198 3.19e-05 ***
## category_code_LT01_14_count  0.12243    0.32799   0.373    0.709    
## category_code_LT01_15_count  0.13788    0.75075   0.184    0.854    
## category_code_LT01_16_count  1.09324    1.16571   0.938    0.349    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.385 on 491 degrees of freedom
## Multiple R-squared:  0.6262, Adjusted R-squared:  0.6216 
## F-statistic: 137.1 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count 0.608062769921894 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0448 -0.7860 -0.0034  0.9298  4.0304 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01152    0.08866 112.918   <2e-16 ***
## category_code_LT01_4_count   1.06339    0.07172  14.826   <2e-16 ***
## category_code_LT01_5_count   0.93540    0.06339  14.756   <2e-16 ***
## category_code_LT01_12_count  0.19824    0.20870   0.950    0.343    
## category_code_LT01_13_count  0.14235    0.24815   0.574    0.566    
## category_code_LT01_14_count  0.12017    0.33426   0.360    0.719    
## category_code_LT01_15_count  0.36492    0.76359   0.478    0.633    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.41 on 491 degrees of freedom
## Multiple R-squared:  0.6128, Adjusted R-squared:  0.6081 
## F-statistic: 129.5 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_16_count 0.608859926289401 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0430 -0.7989 -0.0057  0.9305  4.0301 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01175    0.08857 113.036   <2e-16 ***
## category_code_LT01_4_count   1.06320    0.07061  15.058   <2e-16 ***
## category_code_LT01_5_count   0.93255    0.06336  14.717   <2e-16 ***
## category_code_LT01_12_count  0.19561    0.20848   0.938    0.349    
## category_code_LT01_13_count  0.14423    0.24757   0.583    0.560    
## category_code_LT01_14_count  0.14009    0.33429   0.419    0.675    
## category_code_LT01_16_count  1.31318    1.18429   1.109    0.268    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6136, Adjusted R-squared:  0.6089 
## F-statistic: 129.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_13_count+category_code_LT01_15_count+category_code_LT01_16_count 0.608931034272856 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0433 -0.7979  0.0110  0.9379  4.0318 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01005    0.08848 113.131   <2e-16 ***
## category_code_LT01_4_count   1.06267    0.07020  15.139   <2e-16 ***
## category_code_LT01_5_count   0.93543    0.06306  14.834   <2e-16 ***
## category_code_LT01_12_count  0.20343    0.20786   0.979    0.328    
## category_code_LT01_13_count  0.15168    0.24803   0.612    0.541    
## category_code_LT01_15_count  0.39273    0.76301   0.515    0.607    
## category_code_LT01_16_count  1.30681    1.18329   1.104    0.270    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.408 on 491 degrees of freedom
## Multiple R-squared:  0.6137, Adjusted R-squared:  0.6089 
## F-statistic:   130 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_12_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.608767592699928 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0441 -0.8004 -0.0116  0.9332  4.0299 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01194    0.08858 113.026   <2e-16 ***
## category_code_LT01_4_count   1.06435    0.07070  15.054   <2e-16 ***
## category_code_LT01_5_count   0.93385    0.06335  14.740   <2e-16 ***
## category_code_LT01_12_count  0.20058    0.20843   0.962    0.336    
## category_code_LT01_14_count  0.13732    0.33434   0.411    0.681    
## category_code_LT01_15_count  0.36005    0.76172   0.473    0.637    
## category_code_LT01_16_count  1.30484    1.18417   1.102    0.271    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6135, Adjusted R-squared:  0.6088 
## F-statistic: 129.9 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################
## ########################################
## category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 
## approval_real_price_sum_by_by_approval_type_LT01 ~  category_code_LT01_4_count+category_code_LT01_5_count+category_code_LT01_13_count+category_code_LT01_14_count+category_code_LT01_15_count+category_code_LT01_16_count 0.608357043372209 
## 
## Call:
## lm(formula = multiple.formula_str %>% as.formula, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.0489 -0.8032  0.0091  0.9276  4.0283 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                 10.01361    0.08860 113.015   <2e-16 ***
## category_code_LT01_4_count   1.07220    0.06995  15.327   <2e-16 ***
## category_code_LT01_5_count   0.93836    0.06314  14.861   <2e-16 ***
## category_code_LT01_13_count  0.15896    0.24811   0.641    0.522    
## category_code_LT01_14_count  0.16230    0.33355   0.487    0.627    
## category_code_LT01_15_count  0.38084    0.76356   0.499    0.618    
## category_code_LT01_16_count  1.33698    1.18550   1.128    0.260    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.409 on 491 degrees of freedom
## Multiple R-squared:  0.6131, Adjusted R-squared:  0.6084 
## F-statistic: 129.7 on 6 and 491 DF,  p-value: < 2.2e-16
## 
## ########################################